Turkey has been an importer of beef since 1985 when trade barriers were lowered, until 1996. In 1997, an import ban came into effect and prohibited significant imports. From 1985 to 1996 imports covered between 3 and 15 percent of domestic consumption. For this period, a price series of import prices was calculated from Turkish import statistics. For 1989 to 1996, import unit values of frozen compensated beef quarters were taken as indicators for the average import price, as significant quantities of this product were imported in each of these years. For the years 1985 through 1988, import unit values for fresh meat of bovine animals were taken, as no significant quantities of frozen quarters were traded. This approach is justified by the fact that the unit value for the two products were reasonably close in the years 1989 to 1991. Table 6.12 presents price data for beef.

**Table 6.12: Turkish Import, Border, and Domestic Prices for Beef (US\$/t)**

Sources: SIS (import statistics); UFT (tariffs); OECD (farmgate price); own calculations.

Tariffs and a transportation margin (as applied in **TURK.SIM)** are added to the import price in order to generate a duty paid border price at wholesale level to be compared to the internal price, which is generated by adding a wholesale margin (as applied in TURKSIM) to the OECD reported farmgate price.53 The border price and the internal wholesale price are presented graphically in Graph 6.9.

53 There is no reason, of course, to assume that such a margin should stay constant over time. No empirical information, however, on the development of such a margin was available.

**Graph 6.9: Turkish Border and Internal Wholesale Prices for Beef, 1985-1996 (US\$/t)**

Graph 6.9 shows that the internal price usually lies above the border price and follows, to a certain extent, the movement of the border price. This positive price correlation can especially be observed, independently of the overall trend of increasing beef prices, in the years 1987 to 1990 and 1995 to 1996, when prices deviate from the overall increasing trend. The 1994 internal price is distorted due to a strong devaluation of the Turkish Lira in 1994, so 1994 is not included in the data set for estimation.

The years 1990 to 2000 were a period of dairy product imports exceeding one percent of raw milk equivalent of domestic milk consumption in most years. A price series of duty paid border prices was created for this period using Turkish import unit values for **SMP** (CN position 04021019) and butter (CN position 04050011) as indicators for the average price level of imported dairy products. The results are presented in Table 6.13. The tariff-paid border prices for butter and SMP are aggregated by weighting them with their relative extraction factors, and a transportation margin is added as applied in TURK.SIM in order to create a border price per ton of raw milk equivalent at wholesale level. A processing margin as applied in TURK.SIM is added to the fanngate price in order to create an internal price at wholesale level for comparison to the border price. The

Sources: Various sources (see below); own calculations.

processing margin is rather large and even exceeds the farmgate price in one year. This wholesale margin was calculated for the base period of TURK.SIM (see Subchapter 7.2 below); for the purpose of this analysis it is assumed to be constant in dollar terms over the period 1990 to 2000. Therefore the internal price at wholesale level could be distorted, as the reasons for such a high margin and its development over time are obscure. An alternative would be the direct use of observed, internal SMP and butter wholesale prices. This approach, however, has not been followed as SMP prices in Turkey are neither collected nor published. Rather TURK.SIM base period data were collected from individual companies (see Subchapter 7.2).

**Table 6.13: Turkish Import, Border, and Domestic Prices for Dairy Products (US\$/t)**

Sources: SIS (import statistics); UFT (tariffs); OECD (farmgate price); own calculations.

The border price and the internal wholesale price are presented graphically in Graph 6.10. Graph 6.10 shows that the internal price is above the border price for the whole period, except for the year 2000. The correlation, however, is less clear than in the case of beef. During periods 1992 to 1993 and 1999 to 2000 prices, move in opposite directions, whereas correlation is positive in other periods.

**Graph 6.10: Border Price and Internal Wholesale Price for Milk, 1989-2000 (US\$/t)**

Sources: Various sources (see below); own calculations.

In order to quantify the relationship between the internal price and the border price the following statistical model was estimated in GAUSS using the least squares estimator.

with PI being the internal price, PB being the border price and t being the respective year. The trend parameter y is included as a simple approach to account for the nonstationarity of price series. ~ is the price transmission elasticity of the internal price with respect to the border price. Estimation results are presented in Table 6.14. In the case of beef, the price transmission elasticity is estimated at 0.66, significant at a 5 percent level. The explanatory value of the chosen model is high, as the adjusted R-square is at 0.93 and the F-value is at 69. The Durbin Watson test is inconclusive but the Breusch and Godfrey test for autocorrelation rejects first order autocorrelation at the five percent significance level. The result is in accordance with a priori assumptions that domestic prices are linked to border prices, but price transmission is not complete. Price transmission elasticities for meat in TURK.SIM are therefore set at 0.66.

**Table 6.14: Estimation of Price Transmission Elasticities for Beef and Milk**

\* = significant at 5 percent level.

Source: Own estimates.

In the case of milk, no significant results are obtained from full period data 1990 to 2000. If, however, periods 1990-1993 and 1999-2000 are excluded, the resulting price transmission elasticity is at 0.8 and significant at five percent, and first order autocorrelation is rejected by the Durbin Watson as well as the Breusch and Godfrey tests. The exclusion of 1999-2000 can be justified by the sudden devaluation of the Turkish Lira, but not so the exclusion the period 1990-1993. Nonetheless the price transmission elasticity for milk and eggs in TURK.SIM is set at 0.8. This is because no better a priori assumption exists and it seems plausible that price transmission for milk products and eggs is somewhat higher than that for meat due to lower transportation cost for these products ( e.g. in the form of SMP or dried eggs).

# 7 **DATA SET FOR MODEL CALIBRATION**

The base period for TURK.SIM with respect to the quantitative framework (yield, area, supply, trade, and demand) is the average of the years 1997 through 1999 for plant products and the average of the years 1998 through 1999 for animal products. A two year average is considered sufficient for animal products; animal production is much less volatile than plant production as it depends less on climatic conditions of the respective year. For prices, wholesale as well as farmgate, and the relevant price margins, the average of the years 1996/98 was chosen in order to make allowance for some lagged adjustment at the supply side, which is of course more distinct in animal production due to the respective production cycles and long-term investment decisions. For some products the base period was adjusted for specific reasons which are explained below in the respective sections.

### **7.1 Supply, Trade, and Demand**

# 7 **.1.1 Supply**

### **<IP_ADDRESS> Standard Approach**

Area and yield of plant products and supply of animal products are taken from *Agricultural Structure* yearbooks (SIS, various issues) for 81 provinces and data is aggregated at the level of nine agricultural regions (sum for area and supply; area weighted average for yield). In some cases, when published data include obvious errors of data collection or processing, adjustments are made based on plausibility considerations. Resulting national totals are checked for consistentcy with published national data. Annex Table A-7.1 presents base yield, area, and supply for all regions as well as national totals. For the processing outputs supply is based on *Agricultural Structure* for cotton lint and cottonseed and on FAO commodity balances (FAO, 2002a, b) for oils and oil cakes.

### **<IP_ADDRESS> Specific Cases**

*Vegetables:* SIS publishes production quantities of vegetables, but not product specific area and yield data. Product-specific area data is obtained by SIS on a national level but is not available at regional level. In order to depict regional competition for area with crops and fruit in TURK.SIM, regional area and yield data is generated by calculating national yield data from national area and production quantities, and assuming yield to be similar across regions. Regional area is calculated from regional quantity data divided by national yield data.

*Fruit:* For fruit, SIS publishes only numbers of trees and supply quantities, not area and yield data. Estimates of the national average number of trees per ha are obtained from MARA and are assumed to be similar across regions. Table 7.1 shows the number of trees per ha.

Source: Interviews at MARA.

In order to consider competition for area with crops and vegetables in TURK.SIM, product specific regional area and yield data is calculated by dividing the regional number of trees by the average national number of trees per ha and by dividing the regional production quantity by the resulting regional area.

*Durum wheat:* Area and yield data for wheat are published by SIS for total wheat, including common and durum wheat. Based on interviews with officials of the Turkish Grain Board, the assumption is made that 20 percent of Turkey's total wheat area is allocated to durum wheat uniformly across all regions, and yield is assumed to be as high for durum as for common wheat.

*Sugar:* Sugar beet yield reported by SIS is transformed into sugar using an extraction factor of 12 percent based on F AO (2002b ).

*Tomato paste:* Production of tomato paste is not published by **SIS.** Production data therefore comes from USDA (various issues) and is broadly in line with data published by TOMATO NEWS (2002). 22,000 tons of estimated home production are added to the USDA data (TOMATO NEWS 10/94). As shown in Table 7.2 tomato paste production is highly volatile.

Table 7.2: Tomato Paste Production Quantities and Prices, 1997-2001

Sources: Tomato News (1994); USDA (GAIN Reports, various issues); own calculations.

As the average of tomato paste production in the **TURK.SIM** base period 1997 to 1999 is close to the average of the longer period 1997 to 2001, it is taken as base quantity for TURK.SIM. The yield of paste tomatoes is assumed to equal the yield of table tomatoes and the area for paste tomatoes is calculated by assuming an extraction factor of 1 kg paste out of 5.5 kg tomatoes, which is reported by USDA (various issues). 80 percent of tomato paste area is allocated to the Aegean agricultural region (USDA GAIN Report TU1028, 19.05.2001, p. 2). The other 20 percent are allocated to the other regions according to their shares in total tomato area. The regional area for table tomatoes is calculated as the residual of total regional tomato area minus the area for paste production.

*Olive oil:* Production of olive oil is not published by SIS. Production data therefore comes from the IOOC (2002) and is broadly in line with data published by USDA (various issues). Due to the high volatility of production (see Table 7.3) a four year average of the years 1997 to 2000 is used for calibration of production (as well as consumption and trade) in **TURK.SIM.**

**Table 7.3: Olive Oil Production Quantities, 1997-2001**

Sources: IOOC (2002); own calculations.

The yield of olives for oil is assumed to equal the yield of table olives, and the area for olive oil is calculated by assuming an extraction factor of 1 kg oil out of 6 kg olives. FAO (2002b) reports an extraction factor of 7 in its commodity balances, but experts from the industry in Turkey report a factor of 5. National area for oil olives is allocated to regions according to their area shares in total olive area. The regional area for table olives is calculated as the residual of total regional olive area minus the area for oil production.

*Sultanas:* Production of sultanas is not published by **SIS.** Production data therefore comes

from GAIN Reports of the USDA (various issues). Due to data availability an average of the years 1999 to 2000 was taken for calibration. The yield of sultana grapes is assumed to equal the yield of table grapes and the area for sultana grapes is calculated by assuming an extraction factor of 1 kg sultanas out of 4.5 kg grapes. National area for sultanas is allocated completely to the Aegean • *"54* region.

*Red meat:* Data published by SIS for red meat underestimates total production as only data of municipal slaughterhouses and estimates for slaughtering for religious festivals are included. This underestimation is especially significant in the case of sheep meat, for which more than half of total production falls outside the SIS statistics. Therefore FAO (2002a) estimates of total production are used. Indigenous meat production is calculated by adding the meat equivalent of live animals exported minus the meat equivalent of live animals imported. Production is allocated to agricultural regions by applying the shares resulting from provincial production data reported by **SIS.**

*Poultry and eggs:* For poultry meat and eggs estimates of BESD-BIR, the Association of Turkish Poultry Producers are used, which are about 20 percent above official data for poultry and about 20 percent below official data for eggs. Production is allocated to agricultural regions by applying the shares resulting from SIS reported provincial production data.

# **7.1.2 Trade**

Trade data is for the same period as production data and is taken from F AO and identical with the data provided from SIS. For a few products trade data is directly taken from SIS trade statistics. If the relevant processed products are not modeled explicitly and if data is available, trade data is taken from F AO commodity balances. For these balances, trade data of the primary products as well as relevant processed products is aggregated to its primary equivalent. For example wheat trade includes the traded wheat equivalent of flour, pasta, bulgur, and so on. This approach is especially important as human demand in Turkey is calculated as a residual (see below) and therefore consumption figures would be distorted without consideration of trade in processed products. All trade data is presented in Table A-7.2 of the Annex.

54 USDA (various issues), GAIN Report TU2018, 22.04.2002, p. 2.

# **7.1.3 Demand**

### **<IP_ADDRESS> Processing Demand, Seed Demand and Waste**

Seed demand is fixed as a quantity per area unit for plant products, and per supply unit for eggs and waste is defined as a fixed percentage in TURK.SIM. All data, except processing demand for cotton, which equals farm supply of cotton, is taken from F AO commodity balances (2002a, b ). Processing demand, seed demand, and waste are presented in Table A-7.2 of the Annex.

#### **<IP_ADDRESS> Feed Demand**

The relevant input for the calibration of TURK.SIM are the quantities of feed components per animal unit produced. This data is obtained in three steps:

National total feed component quantities are taken from F AO commodity balances. The shares of individual animal products in total component demand are based on OECD data used for PSE calculations and on several USDA GAIN reports on poultry and livestock production (USDA, various issues) reporting total feed use and feed ratios. Table 7.4 presents total feed demand, feed demand per animal product, and feed demand per animal product unit. Table 7.4 shows, that about I 0.5 million tons of the products covered by TURK.SIM are used for feed consumption with about 45 percent covered by barley. About 40 percent of total feed is used in milk production. When looking at feed demand per animal unit it is interesting to note that the use of grains in bovine meat production is relatively high compared to European averages. This is due to the low use of fodder in cattle feeding in Turkey and is confirmed by specific rations (Grethe and Uzmay, 2000, p.40). The use of feed components in poultry and egg production, on the other hand, is close to international averages.

Sources: FAO (2002b); OECD (unpublished); USDA (various issues); own calculations.

For the determination of cross-price elasticities, value shares of feed components are calculated (see Section 6.3.3). Based on USDA published ratios about 8 percent of the total value of feed for poultry and egg production are assumed to stem from other products than those covered by TURK.SIM. For ruminants much of total feed requirements are covered by coarse feed, but no publications with respect to quantities and the value share of coarse feed in total animal feed were found. Therefore a simple three step approach is followed in order to roughly estimate the value share of coarse feed in ruminant production:

by **TURK.SIM.** This is because a high share of the production factors used in coarse feed production has low opportunity cost ( e.g. extensive pasture land and unpaid family labor).

In order to illustrate the calculation of nutrient requirement and the resulting value share of coarse feed in total feed, the example of milk is presented below. For milk the daily nutrient requirement per cow is calculated according to

NEL MJ/day = 0.293 • kg Jive weight0· 75+ 3.37 • liter milk. 55

For Turkey milk production per animal is around 1620 liter per animal per year and live weight is about 400 kg. Therefore the nutrient requirement in NEL MJ is about 9300 per ton of milk. About 2100 NEL MJ are covered by the ration presented in Table 7.4 which is about 23 percent of total nutrient intake. Thus, 77 percent of nutrient intake are covered by coarse feed and as the value per nutrient unit is assumed to be 50 percent of the value of nutrient from other feeds the resulting value share is about 63 percent.

For bovine meat and for sheep meat production, the calculation of nutrient requirement is also based on KIRCHGESSNER ( l 992). Resulting nutrient shares and value shares are presented in Table 7.5.

**Table 7.5: Nutrient and Value Shares of Coarse Feed in Total Feed for Ruminants**

Source: Own calculations.

### **<IP_ADDRESS> Human Demand**

Human demand is calculated as the residual of production minus waste, seed demand, feed demand, processing demand and net trade. Total human demand is allocated to income quintiles according to data observed for some products and assumptions made for others. Human demand per income quintile as well as the base principles for allocation to quintiles are presented in Table A-7 .3 of the Annex.

For some products such as wheat and all animal products, allocation to quintiles is done according to the data from the 1994 expenditure survey. For other products the allocation to quintiles is assumed to be the same as for products

55 Kirchgessner (I 992, pp. 281 and 284). NEL = Nettoenergie Laktation; MJ = Megajoule.

observed. For example in the case of basic food commodities like pulses, maize, and potatoes, the distribution is assumed to equal that observed for wheat, and a product with a higher income elasticity like cotton lint is assumed to be distributed like poultry meat. For some products, like fruit and vegetables, the distribution is assumed to equal that of an observed product with the total spread being lower, because the income elasticity used in **TURK.SIM** is lower. For all oils except olive oil, the distribution among quintiles is assumed to be equal relative to the effective household members, as no significant income dependency of the quantity consumed was found from the observed data. The fact that the distribution among household quintiles for these products of "equal distribution" is not equal across quintiles (see Table A-7.3) is due to quintiles containing an equal number of households each, but the number of effective household members per quintile being different due to household size.

For the establishment of cross-price elasticities of demand, the respective value shares of consumption are used (see Section <IP_ADDRESS>). Thus total expenditure per income quintile is required. Total expenditure per income quintile is taken from the 1994 expenditure survey, adjusted for GDP growth between 1994 and 1998, the average base year of the quantity framework, and expressed in 1997 TL, like all other monetary parameters and variables in TURK.SIM. The results are shown in Table 7.6.

**Table 7.6: Total Expenditure and Food Expenditure per Income Quintile**

Sources: SIS (1997); own calculations.

Table 7.6 shows that overall expenditure in the base period was about one billion TL in quintile 1 and five billion TL in quintile 5. The value shares of food expenditure in total expenditure, which result from multiplying base consumption quantities in TURK.SIM by base wholesale prices, are between 57 percent in quintile 1 and 23 percent in quintile 5. These shares are surprisingly high compared to the shares of food expenditures published in the 1994 survey and shown in row three of Table 7.6. One would expect the shares resulting from TURK.SIM base data to be much lower than those from the 1994

expenditure survey for two important reasons: i) some food products like fish and goat meat are not included, and ii) the processing share is only partially included as products are valued with their respective wholesale prices, while many products are sold to households as higher processed products ( e.g. cookies, sausages). On the other hand, consumption data in **TURK.SIM** includes out-of-home consumption as consumption is determined as a residual, in contrast to food consumption in the expenditure survey which excluded out-ofhome consumption. One other possible explanation of the low share of food expenditure reported in the 1994 survey could be a significant underestimation of subsistence production. Finally, the reason for the somewhat high shares of food expenditure in **TURK.SIM** resulting from the combination of 1994 expenditure data and 1997 to 1999 consumption data is not clarified. Therefore data is used as presented in the first two rows of Table 7.6.

### 7.2 **Domestic Prices, Trade Prices, and Margins**

Annex Table A-7.4 presents all prices, price margins, and price policies expressed in €/t which apply in the base period. The trade position in the base period is indicated in Column 20, and shows whether the import or the export price was an observed price in the base period.

### **7.2.1 Domestic Prices**

Domestic farmgate prices are presented in Column 1 and sources are presented in Column 21 of Table A-7.4. In most cases prices stem from published farmgate price statistics in *Agricultural Structure* (SIS, various issues), and, for common and durum wheat, from unpublished SIS farmgate price statistics. Red meat prices are from OECD (2002a) PSE data as SIS published prices are distorted due to the collection method. 56 For tomato paste the observation ofraw input accounting for 40 percent of the wholesale price reported by USDA ( various issues) is used for calculation of the farm gate price. For sugar the SIS observed farmgate price for sugar beet is divided by 0.12, the Turkish extraction rate, in order to determine the farmgate price for sugar equivalent. The farmgate price for olive oil equivalent is calculated by deducting a processing margin of €350 from the wholesale price and the farmgate price for table olives is calculated from the SIS reported average price for total olives and the resulting price for oil olives. The farmgate price for sultana grapes is determined by deducting a processing margin of €120 from the SIS reported wholesale price,

56 SIS data is collected at the end of the year from slaughterhouses. In a situation with yearly inflation rates between 50 and I 00 percent, the application of average yearly exchange rates/price indices to this data is distortive. More precise information on the period of validity of collected price data would be necessary.

and the price for dried tea is the SIS-reported price for green tea divided by the SIS-reported extraction rate of 18.3 percent.

Wholesale prices are reported in Column 7 of Table A-7.4 and sources are given in Column 22. For most products they are taken from *Wholesale Price Statistics*  **(SIS,** various issues). For some others the processing margin is based on assumptions and the wholesale prices are calculated as farmgate prices plus processing margin. This is due to the fact that for some products no wholesale data is available, and for some products wholesale prices reported are not consistent with farmgate prices (i.e. farmgate prices higher for some products without any specific policies, like food subsidies, in place). For oil cakes, cottonseed, and soybean oil, for which no domestic prices are available, import or export unit values (IlJV, EUV) and the respective border policies are used to approximate the domestic wholesale price. The cotton wholesale price is calculated by weighting the wholesale prices of seed and lint with the respective extraction shares. For milk the wholesale price is calculated by weightinf the wholesale prices of butter and SMP with their respective extraction shares.5 The butter price is from the SIS and the SMP price is from Turkish dairy companies as no official price statistic exists.

# **7.2.2 Trade Prices**

Import or export prices are calculated for each product dependent on the net trade position as unit values from unpublished external trade statistics obtained from the SIS, and are presented in Columns 8 and 14 of Table A-7.4. Standard CN-positions are chosen in order to reflect average trade qualities which are as comparable as possible to domestic products. For sheep meat, only small quantities are exported and reported export unit values are far above international prices. Therefore the import unit value of the EU is chosen as the relevant international price. Also for sugar, barley, and durum wheat, Turkish export unit values are far above international prices and EU export unit values are therefore chosen as world market prices. The assumed cif-fob spread is presented in Column 13 of Table A-7.4 and it is added or subtracted from the observed trade price in order to create an international price for the reverse trade position.

# **7.2.3 Margins**

The total processing margin, which separates the farmgate price from the wholesale price, is presented in Column 6 of Table A-7.4. This margin is an observed margin in those cases, where farmgate price and wholesale price are

57 For butter, 0.0442; for SMP, 0.091.

observed prices. In other cases, in which only the farmgate price or the wholesale price is observed, the processing margin is fixed based on assumptions. The processing margin consists of three elements (see Section 5.2). The part resulting from waste of the raw product is not presented separately in Table A-7.4. The other two components are presented in Columns 4 and 5.

The quality margins in the base situation, which are calculated by TURK.SIM as residuals (see Section 5.2.1), are presented in Columns 10 and 17 of Table A-7.4 and are identical for importing and exporting situations.

### **7.3 Base Period Policies**

### **7.3.1 Tariffs**

Specific and ad valorem tariffs of the base situation are taken from Tariff Schedules obtained from the Undersecretariat of Foreign Trade (various issues), and are presented in Columns 15 and 16 of Table A-7.4.

### **7.3.2 Export Subsidies**

Explicit export subsidies applied for part of the base period for potatoes, onions, tomatoes, processed tomatoes, citrus fruit, olive oil, poultry, and eggs. The total outlays per product category are taken from notifications at the WTO (various issues), and are divided by total base period exports in order to calculate the per unit rates presented in Column 9 of Table A-7.4. Per unit rates are rather low with about €53 per ton being the highest rate (tomato paste).

For some products, however, high differences between low export prices and high domestic prices are difficult to explain by quality differences. As state trading enterprises were actively involved in exports of the products concerned during the TURK.SIM base period, part of the difference is considered an implicit export subsidy covered by budgetary losses through state trading enterprises. These products and the respective price differences implemented in TURK.SIM are presented in Table 7.7.

**Table** 7.7: **Products with Implicit Export Subsidies**

Source: Various sources; own calculations.

For barley and for tobacco the assumption is made that 25 percent of the price gap is due to quality (Column 5 of Table 7.7), and the other 75 percent is an implicit export subsidy. For sugar, no quality margin is assumed due to the homogeneity of the product. For tea, the assumption is made that 62 percent of the price gap is due to quality, and the rest is an implicit export subsidy.

# **7.3.3 Producer Premiums**

As for prices, the base period 1996 to 1998 is chosen for producer premiums as producers usually get information on the level of payments after having made their production decisions. In this period, direct payments were granted only for milk and tobacco, and product-specific budgetary outlays were obtained by the Agricultural Ministry. Only for milk the rate per product unit is significant. It is at €3.9 per ton as presented in Column 2 of Table A-7.4.

# **8 PROJECTION SCENARIOS**

Several parameters are necessary in order to project production, consumption, and trade for the year 2006. Assumptions on changes of world market prices between the base period and 2006 are described in Subchapter 8.1 and shifters applied to production and consumption are discussed in Subchapters 8.2 and 8.3. The assumptions made for the projection of effects resulting from the development of the Southeast Anatolia irrigation project are presented in Subchapter 8.4.

Finally, along with these projections which are assumed not to be affected by Turkish agricultural policies, three agricultural policy scenarios are defined and analyzed for their effects in the year 2006. First, a status quo scenario with largely unchanged policies provides a reference for comparison with other options. Second a liberalization scenario is defined in which Turkey abolishes all market policies like tariffs, export subsidies, and coupled premiums. Third a CU scenario with agriculture being in the CU with the EU is analyzed:

#### **Status Quo**

#### **Liberalization**

• Abolition of all tariffs, export subsidies, and premiums.

#### **Customs Union**

58 WTO commitments stem from the Uruguay Round only and no assumptions are made with respect to outcomes of the current Doha Round of WTO negotiations. This is because the beginning of any further reduction commitments seems implausible before 2006 (the TURK.SIM projection horizon) as Turkey's current commitments will not be fully implemented before 2004 and, at the time of finishing this study in February 2003, an agricultural agreement still seems distant.

• If an increase in the domestic price in Turkey generates an export surplus for a product for which the EU is projected to be a net exporter and to which it applies supply control measures, Turkey would have to constrain supply in order not to exceed domestic demand.

Detailed assumptions on Turkish and EU agricultural policies and their effects on Turkish border prices are discussed below in Subchapters 8.5 and 8.6.

### **8.1 World Market Prices**

Turkish import and export prices in 2006 are calculated based on base period 1996/98 border prices adjusted for projected changes in real world market prices. The world market price changes assumed for TURK.SIM are based on projections of the F APRI, the OECD and the World Bank. World market price projections and assumptions for TURK.SIM are presented in Table 8.1. Price projections are also reported for some products not covered by TURK.SIM but with close substitution relationships with those in TURK.SIM, for example rapeseed and rapeseed oil. For most products, changes in TURK.SIM are based on the average of available projections. In some cases, changes in TURK.SIM are based on projected changes for other products (e.g. sunflower seed cake). In the case of barley, where only one projection is available which would result in a major change of relative cereal prices, a smaller change is assumed. For products where no projections are available, like fruits and vegetables, real prices are assumed to stay constant in real terms.

59 This assumption is based on the observation that nominal EU support prices have not been adjusted for inflation during recent years.

#### **Table 8.1: World Market Price Projections and Assumed Changes in Real World Market Prices for TURKSIM, 1996/98 to 2006 (percent)**

n.a.: Not available.

• Product not covered by TURK.SIM.

Sources: FAPRI (2002); World Bank (various issues); OECD (2001d); own calculations.

# **8.2 Shifters at the Supply Side**

Table 8.2 shows the observed growth rates of yield, milk production per cow, carcass weight of sheep and cattle, and egg weight, as well as the productivity growth rates assumed for TURK.SIM.

#### **Table 8.2: Growth Rates 1968 to 1998 and Assumed Productivity Shifter**

Sources: F AO database; own calculations.

In most cases, yield growth rates have been high for plant products in the 1970s and 1980s, and slowed down in the 1990s. In those cases, the growth rates observed in the 1990s are assumed to continue until 2006. In some cases however, like cotton, for which growth rates in the 1990s were especially high, growth rates are assumed to decline until 2006. Ad hoc assumptions are made for beef, poultry, and eggs.

### **8.3 Shifters at the Demand Side**

Average yearly population growth for the period 1998 ( quantity base) to 2006 in Turkey is assumed to be at 1.4 percent and is based on observations and projections published by the World Bank (2002). Average annual GDP growth for the period 1998 to 2006 is assumed to be 1.8 percent and is based on OECD (2002a, 2002c ). This is rather low because periods of shrinking real GDP in the years 1999/98 (-4.7 percent) and 2001/2000 (-7.4 percent) fall within this period.

### **8.4 Development of the Southeast Anatolian Irrigation Project**

In order to allocate newly irrigated area to plant production various sources have been used. Both the *Master Plan Study* (STA TE PLANNING ORGANIZATION, 1990) and the more detailed *Marketing Survey and Crop Pattern Study*  (SOUTHEASTERN ANATOLIA PROJECT REGIONAL DEVELOPMENT ADMINISTRATION, 1992) come up with projected cropping patterns which differ significantly. In addition to existing projections, the first cropping patterns established by farmers on newly irrigated land in the GAP region can be observed. The most striking result of such observations is that cotton accounts for about 80 percent of the newly irrigated area. Another fact observed is that farmers plant fewer perennials than expected, demonstrating a higher preference for direct money for cash crops over long-term investments.

For TURK.SIM the parameter ad\_ ha is determined according to the following steps.

• 156,000 ha are available for additional production of products included in the TURK.SIM index irr. Therefore ad\_ha is 156,000 • 1.25 (CI)• 1.5 (yield)= 292,500 ha.

In order to allocate this area TURK.SIM products are allocated to the irrigation indices ( see Section 5 .2.1.1) as follows:

**Table 8.3: Classification of Products into Irrigation Indices**

Source: Own compilation.

The irr \_ w parameters, which determine the share taken at the additionally irrigated area compared to the current area share, are set as shown in Table 8.4.

**Table 8.4: Parameters irr\_w**

Source: Own compilation.

Parameters are set so as to represent results of projections in the *Master Plan Study* and, especially, the *Marketing Survey and Crop Pattern Study* (as well as current observations mentioned above, like the high cotton share).

In order to get an impression of the implications of these assumptions, the resulting crop pattern under the status quo scenario is presented in Table 8.5 and compared to projections made in the *Master Plan Study* and the *Marketing Survey and Crop Pattern Study.* As in the latter study, projections are also made for various points in time before project completion, and projections for the year 2000 are also presented. This may be the most fitting comparison, as 650,000 ha are assumed to be irrigated by 2000 under that study, comparable to the extent of project implementation now assumed to be realized in 2006.

**Table 8.5: Projections of Crop Pattern on Irrigated GAP Area (percent)**

• Including potatoes and onions.

Sources: State Planning Organization (1990, volume I, p. 8); Southeastern Anatolia Project Regional Development Administration (1992, volume I, p.25; volume IV); own calculations.

Projections of this analysis are largely in line with the comparable *Marketing Survey and Crop Pattern Study* projections for the year 2000. The main differences are the much higher share of cotton and the lower share of perennials assumed in this study, based on observations at the irrigated area already available.

#### **8.5 Policies and Price Formation under the Status Quo and the Liberalization Scenarios**

Annex Tables A-8.1 and A-8.2 show prices, price margins and policies under the status quo and the liberalization scenario. Under the status quo scenario, tariffs are reduced compared to their base level if necessary to comply with the 2004 final bound WTO level. Implicit export subsidies for products, for which effectively zero export subsidies are bound in the WTO, are abolished. Other export subsidies are maintained but lowered such that the 2004 final bound levels are not exceeded. The milk producer premium applied in the base period is fully maintained. The sugar quota is set at a level to maintain the domestic price level of the base situation. In the liberalization scenario all market policies are abolished.

### **8.6 Policies and Price Formation under the CU Scenario**

Table A-8.3 of Annex 8 shows prices, price margins and policies under the CU scenario. The general assumptions made on the process of Turkish price formation in a situation wherein agriculture is included in the CU with the EU are discussed above in Sections 4.3.1 and 4.3.2. Specific assumptions made for price formation for each of the products covered are summarized in Table 8.6 and some cases are explained in detail below.

*Cereals:* For cereals the nominal intervention price is at € 101. If inflation is taken into account this will be about €89/t in 2006 (in real 1997 €), which is below all world market price projections for cereals. As the EU is assumed to stay a net exporter of cereals, cereal prices in the EU will not be kept significantly above world market prices in such a situation, and the price in the EU and Turkey will be determined by the world market price and not by the intervention price.

*Pulses, oil cakes, oilseeds, cotton lint:* As the EU applies no tariffs, prices are assumed to be at world market level.

*Tobacco:* In an importing situation, Turkey would charge the EU tariff of about 15 percent for imports originating from third countries or import from the EU at a level of 15 percent above world market price. As the EU is a clear net importer of tobacco the assumption is made that Turkey would import from third countries. In the exporting situation no difference would occur with the non-EU scenarios, as Turkey already has free access to the EU market.

*Sugar:* The sugar price is assumed to be 10 percent below the projected EU intervention price in the exporting situation and 10 percent above the EU intervention price in the importing situation. This situation of market prices in individual EU member countries above or below the intervention price, depending on the net trade situation, has been observed in the past and is also assumed to be valid in the Turkish case.

*Onions:* For an exporting situation, prices are derived as for potatoes with a resulting increase of the export price of 7 .0 percent. In an importing situation, Turkey would probably import from the EU, a major exporter of onions. Therefore, the import price is also assumed to increase by 7.0 percent compared to the liberalization scenario.

#### **Table 8.6: Assumptions on Policies and Price Formation under the CU Scenario**

*Potatoes:* In the importing situation, Turkey would charge the EU tariff (11.5 percent in 2006) for imports originating from third countries, of which the EU itself is an importer, or import at world market price level late potatoes from the EU, as the EU is an exporter of late potatoes. As imports of early as well as late potatoes have been observed for Turkey in the past, it is assumed that Turkey would charge an average tariff of 5. 7 5 percent in an importing situation. For the exporting situation, the resulting price for Turkey is derived as follows. Turkish potato exports to the EU are currently tariff free except for the period 1 April through 30 June, in which the average MFN tariff of 11.5 percent is charged. Without a CU, Turkey would also pay the MFN tariff in 2006 during this period. If this tariff were abolished, Turkey's export price would increase by 11.5 percent in the period concerned. In addition, this would also raise Turkey's market price during the rest of the year as producers and consumers in Turkey would adjust to the new situation. Producers would shift resources to the period in which exports to the EU would become more favorable, and this would reduce supply during the rest of the year. Consumers would substitute some consumption in the period in which exports to the EU would become more favorable for consumption during the rest of the year; demand in that period would increase. As a result, the domestic price in Turkey would also increase in the period not directly affected by the EU tariff reduction. This effect, of course, is difficult to quantify. The approach adopted for this study is to assume the price effect to be the average of the total tariff reduction (11.5 percent) and the tariff reduction multiplied by the share of the year in which the tariff reduction does occur (11.5 percent \* 3/12 (months)= 2.875). As a result Turkey's export price under the CU scenario is assumed to be 7.2 percent higher than under the liberalization scenario.

*Tomato paste:* In an importing situation, Turkey would import tomato paste from the EU, which is a major net exporter of tomato paste, at a price of 14.4 percent above world market level (MFN tariff). According to traders, the price received for paste destined for the EU is about €50/t higher than for exports to third countries. As 25 percent of Turkey's current exports go to the EU, the export price of Turkey is €37.5/t below the EU price. Turkey's export price under the CU scenario is therefore assumed to increase by €37.5/t versus the non-EU scenarios. This approach, however, may overestimate the advantage for Turkey because Turkish exporters were unable to make full use of the EU tariff free TRQ of30,000 t of paste in the years 2000 and 2001.

*Melons:* In an importing situation, Turkey is assumed to apply the EU-tariff of 8.8 percent to imports from third countries, as the EU is a major net importer itself. As Turkish exports of melons are tariff free from 1 April to 15 June, and Turkey has never fully utilized its tariff free TRQ for the balance of the year, the export price is not assumed to be different from the non-EU scenarios.

*Fruits and vegetables covered by the entry price system: table tomatoes, cucumbers, table grapes, apples, oranges, lemons, and mandarins:* The abolition of the entry price system is assumed to have no effect on Turkish prices (see Section 2.2.3). In the case of Turkey being a net importer, the 2007 EU tariffs apply for imports from third countries.

In addition to the entry price system, table grapes are subject to the MFN tariff in the period from 1 May to 17 June and 1 August to 14 November. The average EU tariff for 2006 during this period is 16. 7 percent. Export prices are derived like for potatoes. The expected increase in export price is ( 16. 7 percent + 5/12 \* 16.7 percent)/2 = 11.8. percent.

*Peppers, sultanas, table olives:* For all these products, the tariffs applied are WTO bound EU rates. In the exporting situation no difference would occur with the non-EU scenarios, as Turkey has already free access to the EU market.

*Olive oil:* The EU price projection for 2006 is below the Turkish domestic price in a free trade situation. Therefore world market prices would apply in Turkey, too. This is consistent with price comparisons made above (see Section 2.2.3). On the other hand, Turkey exports significant quantities of olive oil to the EU at only partially reduced tariffs. This supports the assumption, that Turkey would gain from a CU. For this study the assumption is made that Turkey could export olive oil in a CU with the EU for a five percent higher price than outside the CU.

*Hazelnuts:* In an importing situation, Turkey would apply the EU MFN tariff of 3.2 percent to imports from third countries as the EU is a net importer. In an exporting situation, Turkey's export price would increase by 3.0 percent as this is the preferential tariff currently charged by the EU on Turkish hazelnut imports.

*Milk:* The Turkish wholesale price in a net export situation is assumed to be at world market level as the EU has a quota system and would probably not accept tariff free imports. In a net import situation, the Turkish import price is assumed to be 5 percent above the projected EU milk equivalent intervention price in 2006 deducted from butter and Sl\1P intervention prices, and the quality margin is assumed to stay constant compared to the status quo scenario. In 2006 the first step of lowering the milk price as part of the Agenda 2000 process will have taken place. Another two reductions by 2008 are foreseen and a further reduction of 10 percent after that. In such a case the EU price would come closer to the world market price projected for this study.

*Bovine meat:* The EU replaced its intervention price system for bovine meat in July 2002 by a system in which the market price will be supported by private storage aid and border policies. Private storage aid can be opened if the market price falls below 103 percent of the basic price of €2,224/t. In the year 2006 this will be €2,003, below projected world market prices. Furthermore, additional cuts in the basic price are proposed by the EU Commission in its Mid Term Review proposals. Therefore, beef prices are assumed to be at world market level.

*Sheep meat:* In an importing situation, the Turkish price is assumed to be at the projected level in Greece, and in an exporting situation it is assumed to be 10 percent lower.

*Poultry and Eggs:* EU prices for poultry and eggs are close to the world market level. Therefore world market prices are also applied in TURK.SIM in the CU scenario.

*Sunflower seed oil, soybean oil, cottonseed oil:* For soybean and cottonseed oils, the EU is a clear net exporter. Prices are therefore assumed to be at world market level in the CU scenario. For sunflower seed oil the EU is a net importer at an average tariff of 8 percent. However, Turkey already has free access to the EU market under the preferential arrangements. Therefore, a CU would not change Turkey's export price. In an importing situation, Turkey would apply the EU tariff to imports from third countries.

# **9 RESULTS OF POLICY SIMULATIONS**

In this chapter the main results are presented and discussed in a summarized form. Product-specific simulation results under all scenarios can be found in detail in Annex Table A-9. l. In many tables throughout this chapter, changes between scenarios are expressed in relative terms only. In most cases the status quo scenario (2006) is compared to the base situation (1997/99) in order to cover the effects of increasing supply and demand as well as projected changes in world market prices until 2006. The liberalization and the CU scenarios are then compared to the status quo scenario in order to depict the impact of policy parameters on model variables.

First, Subchapter 9.1 describes the development of prices, production, and consumption under the different scenarios. Subchapter 9.2 then depicts the effects on trade and Subchapter 9.3 describes welfare changes under the liberalization and the CU scenarios compared to the status quo scenario. In Section 9.3.3, when aspects of income distribution are discussed, some supplementary data on farm size, which is not part of the model output, is provided in order to analyze effects on income distribution among producers. Finally, in Subchapter 9.4, the impact of reduced marketing margins and changes in the real exchange rate on model results is discussed.

# **9.1 Effects on Agricultural Prices, Production, and Consumption**

# **9.1.1 National Effects Aggregated per Product Group**

Table 9.1 below presents a summarizing overview of the changes of prices, quantities and values under the status quo scenario (2006) compared to the base situation ( 1997 /99) per product group. They reflect the impact of supply and demand shifters as well as projected changes in world market prices and policy adjustments necessary to comply with WTO rules. The most important policy adjustments are the abolition of export subsidies for tea and the significant reduction of export subsidies for barley, tobacco, and table tomatoes.

The first column of Table 9.1 shows average changes in farmgate prices for product groups, where price changes for individual products are weighted by domestic supply quantities under the status quo scenario. The strong decline of the farmgate price for the product group of other crops by 4.8 percent is mainly due to projected declining world market prices for cottonseed and lint, and tobacco (see Subchapter 8.1 ), and the reduction of the export subsidy for tobacco. The rise in the fruit price is due to some products moving from a net export situation to a situation of domestic price formation ( oranges, table grapes, tea). The fall of the vegetable price is due to the reduction of the export subsidy for table tomatoes. On average farmgate prices for plant products in the status

quo scenario are 2.2 percent below the base level. Also for animal products, farmgate prices are on average 2.2 percent below the base level with large differences between products. For sheep meat and beef, prices increase by more than 10 percent in a situation of domestic price formation. This increase is mainly induced by demand shifters (income, population) exceeding supply shifters (productivity). For milk, on the other hand, the farmgate price decreases by almost 16 percent because Turkey moves from a net import position in the base situation to a situation of domestic price formation under the status quo scenario. This is mainly induced by the productivity shifter of supply exceeding the demand shifters for milk.

**Table 9.1: Price, Production, and Consumption Changes: Status Quo Scenario (2006) Compared to the Base Situation (1997/99), (percent)**

Note: See Table 9.10 for specific products in these product groups. Source: Own calculations.

Columns 2 and 3 of Table 9.1 present average quantity effects per product group which are weighted by status quo farmgate prices and consist of two components. First, the supply shifters (productivity and additional irrigation area) result in increasing output quantities in the status quo scenario compared to the base. This effect of shifters only, without any adjustments to new prices, is given in Column 2. Column 3 presents the total effects, including shifter and price effects. The difference between Columns 2 and 3 is the pure effect of changing producer prices.6° For the product group of plant products, shifters induce supply to rise by 13 percent. But as the price for plant products falls by 2.2 percent, the total increase of plant supply is only 11.7 percent. For animal products, the effect of shifters is 17 percent and the total increase of production is 16.6 percent. The price effect of animal production is composed of a decrease brought by decreasing product price, and an increase due to a decreasing feed price compared to the base situation. Column 4 shows the change in production value in the status quo scenario compared to the base situation which amounts to 10. 7 percent for all agricultural products. The supply side of processed products is not included in Table 9.1 because this would lead to double counting as products are already included in the unprocessed form.

Columns 5 to 8 of Table 9.1 show price, quantity, and value changes at the consumption side under the status quo scenario compared to the base situation. Wholesale price changes (Column 5), which are weighted by consumption quantities, are typically somewhat lower than farmgate price changes. This is due to that part of the processing/trade margin which is fixed in absolute terms. The difference between farmgate and wholesale price changes is higher for animal than for plant products as the absolute processing margin is higher for animal products on average, and is particularly caused by the high margin for milk (see Sections 7 .2.1 and 7 .2.3). Column 6 shows that effects of shifters at the demand side exceed those at the supply side except for the product group of other crops. This drives the model in the direction of higher prices due to changes in the net trade situation with higher prices in an importing situation, or a situation of domestic price formation, than in an exporting situation (see Section 5 .3 .1 ). Surprisingly, the price effect of the animal consumption quantity is negative, although the price change of -0.9 percent would suggest an increasing consumption quantity. The reasons for this effect are strongly decreasing prices for vegetable oils (-12 to -14 percent), which are considered substitutes for some animal products. The decrease of vegetable oil prices results from projected world market price changes. On average, wholesale prices for agricultural products decrease by 2.3 percent, the consumption quantity increases by 17.3 percent and the consumption value increases by 14.9 percent under the status quo scenario compared to the base situation.

Table 9.2 shows changes of farmgate prices, production quantity, and production value under the liberalization and the CU scenarios compared to the status quo scenario. With this comparison, quantity changes are purely due to

60 For all product groups the effect of shifters strongly dominates the price effect. Therefore, the comparison of any projection scenario to the base period mainly reflects the assumptions made on shifters which enter the model exogenously.

policy-induced price changes (and the production restricting policy in the case of sugar) as shifters and world market price projections are equal under all projection scenarios.

#### **Table 9.2: Price and Production Changes at Farm Level: Liberalization and CU Scenarios Compared to the Status Quo Scenario (2006), (percent)**

Source: Own calculations.

As Column 1 of Table 9.2 shows, farmgate prices for all product groups decline in the liberalization scenario compared to the status quo scenario. For cereals the decline of 12.2 percent is the highest among plant products, and mainly results from the abolition of tariffs and the export subsidy for barley. In the product group other crops, the average price decrease of 7 .2 percent in a liberalization situation results from the abolition of the export subsidy for tobacco, and the tariffs for sunflower seed and sugar. The fall of the average fruit price by 4.1 percent mainly results from the abolition of the tariff and a strong decline of the price for tea, which falls into this product group, by 65 percent. On average, prices for plant products decline by 6.4 percent compared to the status quo scenario. For animal products the average price decline is 25.2 percent, mainly resulting from strongly decreasing milk and red meat prices whereas poultry meat and egg prices decline only modestly. The degree of price decline is conditional upon the assumptions made with respect to the price transmission elasticities (see Subchapter 6.4). If price transmission elasticities for red meat and milk are set to unity, the average price decline for animal products is even 33.5 percent. The total average decline of farmgate prices in the liberalization scenario compared to the status quo scenario is 11.8 percent.

Under the CU scenario, plant prices decrease by almost the same level for cereals and vegetables whereas they remain constant for fruit and increase by 2 percent for other crops. The large difference for other crops compared to the liberalization scenario results from a much higher sugar price and slightly higher prices for onions and potatoes. For animal products the average decline in farmgate prices in the CU scenario is 10.6 percent compared to the status quo scenario, which is still about 15 percentage points above the liberalization scenario. This is due to the protection granted for sheep meat and for milk in a CU scenario. The overall price decline for agricultural products under the CU scenario is 4.7 percent, less than half the level of the liberalization scenario.

Column 3 of Table 9.2 shows that the farm supply quantity of all product groups falls in the liberalization scenario which is in conformity with the decreasing price level for all products. Compared to the significant price reduction of 7 .2 percent for other crops, the decrease in quantity of 0.6 percent is surprisingly small. This is because the price reduction for other crops is mainly due to the decreasing sugar price, which has only a limited production effect because the shadow price is 31 percent below the farmgate price in the status quo scenario. For fruit, the reduction of quantity is as much as that for vegetables (1.1 percent), although the price reduction for fruit is more significant. This can be explained by the fact that most of the price reduction for fruit is due to tea, which has a very low supply elasticity (see Section <IP_ADDRESS> ). Altogether plant production decreases by 1.8 percent under the liberalization scenario compared to the status quo scenario, almost completely due to a decrease of total agricultural area by about 1.7 percent.61 For animal products, farm production under the liberalization scenario is 13.8 percent below the status quo scenario. Under the CU scenario (Column 4), the overall decrease in production is smaller due to less significant price reductions. Especially in the case of animal products, the decrease is only 4.4 percent compared to 13.8 percent under the liberalization scenario. This result is mainly due to smaller reductions for sheep meat and milk prices. In value terms (Columns 5 and 6), agricultural production decreases by 15.2 percent under the liberalization and by 5.4 percent under the CU scenario, if compared to the status quo.

Whereas the results of the comparison of the CU with the status quo scenario for plant products are quite similar to those of CAKMAK and KASNAKOGLU, at least at an aggregate level, results for animal products differ heavily with respect to the order of their magnitude (2001, see Subchapter 4.2). CAKMAK and KASNAKOGLU project Turkish prices for animal products to decline by about 35 percent under the CU scenario, whereas they are projected to decline by only 10.6 percent in this study. Consequently, the decline in production projected by

61 The choice has been made to allow for a modest change in total area instead of keeping it constant. This is because the substitution with fallow land is a real alternative for farmers.

CAKMAK and KASNAKOGLU of 31.5 percent exceeds that found here by several times (4.4 percent, see Table 9.2). These differences seem to result mainly from assumptions made on exogenous parameters rather than the technical nature of the models used. First, CAKMAK and K.ASNAKOGLU (p. 46) use base period prices for model calibration for bovine and sheep meat which are 51 percent and 34 percent above those used in TURK.SIM. This may result from taking SIS reported red meat prices, which are considered distorted (see footnote 56 above). Second, CAKMAK and K.ASNAKOGLU project the price index for animal products to rise by 17.8 percent between the base period and the status quo scenario (p. 34), whereas it is projected to decline by 2.2 percent for almost the same period in this study (see Table 9.1 above). This may be partially due to the fact that CAKMAK and K.ASNAKOGLU obviously limit supply shifters to the effect of additional irrigation area (p. 31) with the result that demand shifters (population and income growth) drive Turkey in the direction of higher prices in an importing situation. Third, the price transmission elasticities set below unity for animal products in TURK.SIM limit the impact of liberalizing agricultural trade on domestic prices.

Table 9.3 shows changes of wholesale prices, consumption quantity, and consumption value under the liberalization and the CU scenarios compared to the status quo scenario.

**Table 9.3: Price and Consumption Changes at Wholesale Level: Liberalization and CU Scenarios Compared to the Status Quo Scenario (2006), (percent)**

Source: Own calculations.

For all individual products, wholesale price changes are smaller than farmgate price changes in relative terms due to the absolute component of the price margin between wholesale and farmgate price. For product groups, however, this is not necessarily the case as can be seen above in the categories of other crops and fruit, for which average wholesale price changes under the liberalization and CU scenarios are above average farmgate price changes. This is a result of wholesale price changes weighted by consumption quantities in contrast to farmgate prices weighted by production quantities. The weighting framework can thus differ due to trade, waste, feed, processing, and seed demand, which make the difference between farm supply and human demand quantities. On average, wholesale prices for agricultural products decline by I 0.4 percent under the liberalization scenario, and 4.4 percent under the CU scenario if compared to the status quo scenario (columns I and 2).

Quantity effects (columns 3 and 4 of Table 9.3) are consistent with price changes except the somewhat surprising result that demand for other crops decreases by only -0.1 percent in a situation of prices increasing by 3.6 percent under the CU scenario. This is because the strong rise in prices of onions and potatoes leads to relatively low quantity adjustments due to low own price elasticities whereas the decreasing tobacco price leads to a high quantity effect due to the high price elasticity applied (see Section <IP_ADDRESS> ). The quantity response to cereal price changes is low, as the own price elasticities of demand for cereals are assumed to be very low. Under the liberalization scenario, total consumption of plant products increases by 3. 7 percent, total consumption of animal products increases by 13.3 percent and total consumption of processed products increases by 2.5 percent compared to the status quo scenario. Under the CU scenario, quantities of animal and plant products decrease less strongly due to higher prices for these products. As a result, food expenditure (at wholesale price level) decreases by 5.2 percent under the liberalization scenario and by 2 percent under the CU scenario compared to the status quo scenario.

#### **9.1.2 National Effects per Product**

Table 9.4 below shows product-specific changes of farmgate prices, production quantities, and production values as well as changes of wholesale prices, consumption quantities, and values under the liberalization and the CU scenarios compared to the status quo scenario.

#### **Table 9.4: Price, Production and Consumption Changes: Liberalization and CU Scenarios Compared to the Status (100 Scenario (2006), percent)**

Source: Own calculations.

Not all results presented in Table 9.4 are analyzed here but some points of special interest are discussed in the following paragraphs.

Table 9.4 shows many quantity changes which can be attributed to cross-price effects on the production as well as at the consumption side. For example the production of durum wheat increases under the liberalization and CU scenarios, although prices are decreasing. This is due to the much stronger price decline of important substitutes like barley and common wheat. Also, increasing production of cucumbers and peppers in cases of constant or declining prices is due to decreasing prices for the substitutes table tomatoes and tomato paste.

The enormous price decline for sugar of 32.7 percent under the liberalization scenario results in only 3.5 percent reduction of production. This result is conditional on the assumption that the shadow price for sugar is at a level of 80 percent of the farmgate price in the base situation (see Section <IP_ADDRESS> ). If the shadow price is assumed to be at 90 percent of the farmgate price level the reduction of quantity in the liberalization scenario would be 11 percent. Under the CU scenario the farmgate price increases even by 2.9 percent compared to the status quo scenario, but the production quantity does not increase as the quota restricts Turkish supply to not exceed Turkish domestic demand. The price for tomato paste decreases in the liberalization scenario due to the abolition of the export subsidy. In the CU scenario, this decrease is much smaller as the abolition of the export subsidy is almost completely compensated by a higher export price to the EU. The price reduction for tea is 65.2 percent under the liberalization and CU scenarios as the EU does not apply any support policies for tea producers. The degree of price reductions is conditional on how the huge difference between domestic price and export price in the base situation is interpreted (see Section 7.3.2). The quantitative response to the price reduction is relatively small ( a negative 19. 7 percent) because the supply elasticity is assumed to be quite small due to limited possibilities for substitution ( see Section <IP_ADDRESS> ).

Prices for animal products decrease significantly under the liberalization and CU scenarios. Output effects are comparably small as decreasing output prices are partially offset by lower feed prices. Table 9.5 shows the changes in the FCI in the status quo scenario compared to the base scenario, and in the liberalization and the CU scenarios compared to the status quo. FCis decline by 9.5 to 17.5 percent under the liberalization scenario. The strong decline for milk is due to a high share of feed components, for which prices decline particularly strong (especially milk, see Section <IP_ADDRESS>). Under the CU scenario, FCis decline less significantly, mainly because of higher barley and milk prices. For eggs, the declining FCI in combination with declining prices for poultry, which is considered a substitute in production due to similar production technology, lead to increasing egg production despite declining egg prices (Table 9.4).

**Table 9.5: Changes in Feed Cost Indices (percent)**

Source: Own calculations.

The development of the oilseed crushing industry is presented in Table 9.6.

**Table 9.6: Changes in Prices and Quantities of Products of the Oil Seed Crushing Industry (percent)**

Source: Own calculations.

Although oilseed prices decline under the status quo scenario compared to the base situation and farm production of oilseeds increases, oilseed crushing declines by 3 .9 percent as oil prices decline so much that they overcompensate the effect of declining oilseed prices. This result is due to the world market price projections which enter TURK.SIM as exogenous parameters. Demand for oil and oilcake increases strongly and imports of these products increase.

Under the liberalization and CU scenarios prices for oilseeds, oilcake, and oils decline, mainly due to the abolition of import protection. Again, the decline in oil prices overcompensate the decline in oilseed prices, and oilseed crushing declines by 4.5 and 3.9 percent, in the respective scenarios. Although oil prices under the liberalization scenario decline by 15.8 percent, oil demand stays almost constant. This is because prices for animal products, especially milk, which are considered substitutes for vegetable oils decrease even more.

#### **9.1.3 Production Effects per Region and Consumption Effects per Income Quintile**

As price formation in TURK.SIM is modelled at a national level and the resulting prices are valid for all regions, effects of regional price differences on production cannot be captured by this analysis. But regional differences of changes in production result from different product composition per region. Table 9.7 presents changes in production value of plant products, animal products, and total agricultural products under the status quo scenario compared to the base situation, and under the liberalization and the CU scenarios compared to the status quo scenario.

**Table 9.7: Changes of Production Value, per Region (percent)**

Source: Own calculations.

For plant products the increase of production value under the status quo scenario compared to the base situation is lowest in east Anatolia at only 2 percent. This is due to the high share of tobacco, for which the productivity shifter is zero and the price declines by 17 .2 percent, and the high share of cereals for which the productivity shifters are low and prices do decline slightly. The production value increases by almost 40 percent in southeast Anatolia, which is mainly due to the newly irrigated area (see Sections <IP_ADDRESS> and 8.4). For animal products, the increase in production value under the status quo scenario is lowest in the Black Sea region due to the high share of milk for which the price decreases by 15 .3

percent, whereas prices for all other animal products increase or remain constant. The increase of production value is highest in the north central region because of a relatively high share of red meat and poultry meat for which prices and production quantities rise significantly. At 5.2 percent, the increase of total agricultural production value is lowest in east Anatolia, and, mainly due to newly irrigated area, it is highest in southeast Anatolia at 32.8 percent.

Compared to the status quo scenario, the Aegean and the Mediterranean regions lose least from declining plant prices under the liberalization scenario due to their high production shares of fruits and vegetables, for which Turkey is a competitive producer. The decline of plant production value is highest in northeast Anatolia with 15.6 percent, which is the region with the highest value share of sugar in plant production, and in the Black Sea region where the value share of tea production is 14.4 percent in total plant production. Sugar and tea are the plant products for which producer prices decrease most under the liberalization scenario. For animal products the decline in production value is between 27 and 44 percent. Regions in which poultry and eggs cover a high share of animal production display a lower decline in production value than others, as poultry and egg prices decline less than those for other animal products. The decline of total agricultural production value is lowest in the Mediterranean region with 10.1 percent due to the favorable composition of plant products there, coupled with a relatively low share of animal products in total production value. It is highest in the north central region, 32.2 percent, due to an unfavorable composition of plant and animal production and a relatively high share of animal products in total production value.

Under the CU scenario, plant production value rises by 1.6 percent in the south central region due to the high value share of potatoes and table grapes, whereas it decreases in all other regions. The decline is highest in the Black Sea region at 11.1 percent due to the high value share of tea, for which the EU does not apply protection. For animal products, the decline in production value varies between 10.6 percent in the south central region and 16.6 percent in the northeast region. Regions which have a high share of milk, poultry, and eggs are relatively better off, as prices for these products decline less under the CU scenario than those for red meat. Total agricultural production value declines least in the south central with 1.4 percent, and most in northeast Anatolia and the Black Sea region, with about 12.4 percent.

Due to differing price and income elasticities per income quintile, consumption quantity reactions to price changes vary among quintiles. Table 9.8 shows changes in food consumption quantity (weighted by wholesale prices of the status quo scenario) and food expenditure ( at wholesale price level) under the status quo scenario compared to the base scenario and under the liberalization and the CU scenarios compared to the status quo scenario.

**Table 9.8: Changes in Food Consumption Quantity and Expenditure, per Income Quintile (percent)**

Source: Own calculations.

The strong increase in food consumption quantity under the status quo scenario, mainly induced by population and income growth (see Table 9.1), is at 20.7 percent in income quintile l and decreases to 14.9 percent in income quintile 5. This is due to lower income elasticities in higher income quintiles (see Table 6.8). The increase in food expenditure is lower, because the average price level for agricultural products under the status quo scenario is lower than in the base situation. Under the liberalization and CU scenarios, food expenditure decreases more in higher than in lower income quintiles, caused by a higher share of animal products for which prices decrease more than for plant products. This effect is partially offset by the fact that own price elasticities are lower in higher income quintiles (see Table 6.9).

#### **9.2 Effects on Trade**

The effects on trade volume of the above discussed changes in consumption and production quantities and the changing world market price pattern between the base situation and the projection scenarios together with the changing import and export price pattern under the CU scenario are summarized per product group in Table 9.9.62

62 For the pure quantity effects on net trade, i.e. net of changes in import and export prices, see Table 9.10.

**Table 9.9: Net Trade by Product Group under Different Scenarios (mill.€)**

Source: Own calculations.

Turkey is an importer of cereals under all scenarios and imports increase by about €230 mill. under the status quo scenario. In case of complete liberalization or a CU, imports increase even more. The higher import level under the CU scenario compared to the liberalization scenario is mainly due to higher feed demand in a situation of significantly higher prices for milk and sheep meat. Net exports of other crops decrease under the status quo scenario, mainly due to the abolition of the export subsidy for sugar and the reduction of the export subsidy for tobacco. Under the liberalization scenario, Turkey is a net importer of other crops, mainly due to the complete liberalization of the sugar market. Under the CU scenario, Turkey is a significant net exporter of other crops as prices for sugar, onions, and potatoes are significantly above those under the liberalization scenario. For fruit and vegetables, as well as for the sum of all plant products, Turkey is a net exporter under all scenarios.

For animal products, Turkey's trade situation is almost balanced in the base situation as well as under the status quo scenario. Under the liberalization scenario, Turkey becomes a net importer of about €1.5 billion of animal products, which decline to about €0.7 billion under the CU scenario due to higher prices for milk and sheep meat.

For processed products, Turkey is a net importer under all scenarios. For agricultural products in total, Turkey is a net exporter in the base situation and under the status quo scenario, but a net importer under the liberalization and the CU scenario.

Table 9 .10 shows quantities of net trade per product under all scenarios.

**Table 9.10: Net Trade, per Product (1,000 t)**

Source: Own calculations.

Changes in traded quantities under the status quo and the liberalization scenario compared to the base situation are modest in most cases compared to the world market volume. Therefore the assumption of Turkey being a small country in a world market context seems justified. Only for milk this assumption could be questioned as the increase in net imports under the liberalization scenario makes up about 4 percent of the world market volume in 200 I and could therefore have a slight effect on world market prices. However, as such an effect would be small, it is neglected in this study. Under the CU scenario, Turkish exports of onions, potatoes, and table grapes to the EU market increase strongly. Also in these cases it is maintained that EU prices stay constant as the change in trade quantity is equivalent to only 5 percent of EU production of onions, 2 percent of EU production of potatoes, and 1.6 percent of EU production of table grapes

Cotton production increases strongly under the status quo scenario compared to the base situation mainly due to the newly irrigated area (see Annex Table 9). Cottonseed processing, however, declines due to the worsening price ratio between processing inputs and outputs (see Table 9.6 above and Annex Table 9). As a result, Turkey becomes a net exporter of cottonseed and a net importer of cottonseed oil and cottonseed cake (Table 9.10). This result is conditional on the world market price projections, and can be questioned as Turkey is an importer for other oilseeds and it seems probable that, in the long run, Turkish cottonseed would at least partially be processed in Turkey.

### **9.3 Welfare Effects**

#### **9.3.1 Effects on Producer and Consumer Welfare**

Changes in producer surplus are chosen as welfare measures at the supply side and they are calculated sequentially as integrals below supply curves. At the demand side, the compensating variation is calculated sequentially as integrals below compensated demand curves. For details, see Section 5.8.2 above. Table 9.11 presents results of welfare changes for producers and consumers under the liberalization and the CU scenarios compared to the base situation.

### **Table 9.11: Change in Total Producer Surplus and Consumer Welfare**

Source: Own calculations.

Under the liberalization scenario, producers of plant products lose about € 1.2 billion, which is equivalent to 5.9 percent of production value under the status quo scenario. Losses for animal producers are higher in relative terms due to higher price reductions and account for about €1.5 billion which is equivalent to 18.5 percent of production value. Together with €51 million in losses for the oilseed crushing industry, total losses for producers amount to about €2.8 billion, equivalent to almost 10 percent of agricultural production value. Consumers, on the other hand, gain from the price reductions under the liberalization scenario. Total gains for consumers amount to about €3.5 billion, equivalent to 11.2 percent of total food expenditure, and exceeding the losses in producer surplus by more than €0.7 billion.63

Under the CU scenario, the total loss in producer surplus is about €1 billion, equivalent to 3. 7 percent of production value, and is exceeded by the improvement in consumer welfare of about €1.5 billion.

Comparing the size of price changes (see Tables 9.2 and 9.3) to the changes in producer surplus and consumer welfare, it turns out that welfare changes are smaller than price changes at the production side and larger at the consumption side. This is logical, because price changes lead to substitution effects as producers and consumers adjust to the new situation according to their profit/utility maximizing behavior. Nonetheless, final welfare changes are

63 Due to the sequential approach of determining the compensating vanat1on, the components resulting from animal and plant price changes cannot be separated correctly as plant and animal products are linked by cross-elasticities on the demand side. This is not the case on the supply side.

surprisingly close to price changes (relative deviation between 7.7 percent for the compensating variation under the liberalization scenario and 26.6 percent for the change in producer surplus for animal products under the liberalization scenario). This is because price changes are in the same direction for most products and substitution effects are therefore limited at the supply as well as at the demand side.

In order to look at the shares individual products have in total welfare changes, effects are also calculated for each product. This is done by taking integrals below each supply and demand curve without taking into account changes in cross prices. With this approach, the overall welfare effects are overestimated (see Section 5.8.1), and therefore, the totals differ from those calculated with the sequential approach. Nonetheless they give a good impression of the contribution of individual products. Product-specific results are presented in Table 9.12 below.

#### **Table 9.12: Change in Producer Surplus and Consumer Welfare, per Product**

Source: Own calculations.

Under the liberalization scenario, common wheat, sugar, and tea account for about 80 percent of the total loss in producer surplus for plant products. These are also the products with the highest losses in producer surplus in relative terms, differing between 13.5 percent of production value of wheat and 59.6 percent of the production value of tea. Among animal products more than half of the loss in producer surplus accrues from milk, although the loss in producer surplus for beef is slightly higher in relative terms. Under the CU scenario, the most significant losses in producer surplus among plant products occur for wheat and tea, in relative as well as in absolute terms. Among animal products beef producers lose most and account for more than 55 percent of the loss of producer surplus for animal products.

At the consumption side, the relative importance of individual products is, in most cases, similar to that at the production side. Exemptions, however, exist due to several reasons. For example, the gains in consumer surplus for barley are much lower than the losses in producer surplus because only a small part of barley supply is used for human demand. The largest part is used for animal feed, and the gains resulting from lower feed prices are part of the change in producer surplus for animal products and do not appear as part of the change in consumer welfare. Another reason for a strong deviation of the dimension of changes in producer surplus and change in consumer welfare can be a very pronounced trade situation. For example, 40 percent of human demand for tea under the liberalization scenario is covered by imports and the change in consumer welfare therefore significantly exceeds the change of producer surplus.

#### **9.3.2 Effects on Budgetary Outlays and Revenue and Overall Welfare Effects**

Changes in budgetary outlays and revenue among the scenarios are due to changes in tariff revenue and in outlays for export subsidies and producer premiums. Table 9 .13 shows budgetary outlays and revenue for each scenario in absolute terms. Changes between scenarios are derived from these values.

Note: Negative figures indicate budgetary outlays. Source: Own calculations.

In the base situation, budgetary outlays exceed tariff revenue. Under the status quo scenario, tariff revenue increases due to increasing imports. Outlays for export subsidies are lower than in the base situation because of the reductions made in order to comply with commitments in the WTO; premiums increase although rates are kept constant because production increases. Under the liberalization scenario, all market policies are abolished and outlays and revenue for the policy categories covered reduce to zero. Under the CU scenario, some tariff revenue results from sunflower oil and sheep meat being imported from third countries because the EU is a net importer for these products itself.

The resulting total welfare effects are presented in Table 9 .14

**Table 9.14: Total Welfare Effects (mill.€)**

Source: Own calculations.

Under the liberalization scenario, total comparative static welfare gains amount to €667 million, or about 2.3 percent of agricultural production value under the status quo scenario. Under the CU scenario, the total welfare gain is €482 million, which is € 185 million less than under the liberalization scenario. This difference stems from two effects: the allocation effect and the terms of trade effect, as defined in Section 4.1.1. The allocation effect can be captured by assuming Turkey applies exactly the same protection level as results from a CU with the EU by introducing MFN trade measures (tariffs, export subsidies), without entering a CU. The terms of trade effect results from Turkey paying higher import prices for some products, which come from the EU instead of the world market, and from receiving higher export prices for some products, which can be exported to the EU instead of the world market. Table 9.15 presents effects of the CU.

**Table 9.15: Terms of Trade and Allocation Effect of a CU, (mill.€)**

Source: Own calculations.

Table 9.15 shows that Turkey's gains from higher export prices for some fruits and vegetables exceed the losses from higher import prices for milk by about €11 million. The overall terms of trade effect, however, is small compared to the allocation effect of a CU, which is at €196 million. This is the welfare loss for Turkey if it were to apply the protection level resulting from the CU without any change in import and export prices compared to the liberalization scenario. It can be calculated as the total welfare effect (-€185 mill.) minus the terms of trade effect (€11 mill.). Alternatively, the allocation effect can be calculated by comparing the hypothetical scenario of Turkey applying the EU protection level without a CU to the liberalization scenario:

Source: Own calculations.

The size of the terms of trade effect depends heavily on the assumptions made about shifters of supply and demand and the resulting net trade position of the products concerned. If supply shifters turn out to be higher or demand shifters turn out to be lower than assumed here, the terms of trade effects would be higher for the export products fruit and vegetables and lower in absolute terms for the import product milk. Table 9.17 shows the impact of assumptions on shifters on the terms of trade effect.

# **Table 9.17: Impact of Shifters on Terms of Trade Effect under a CU**

• For demand shifters "low" represents 1.2 mstead of 1.4 percent of annual population growth, and 1.0 instead of 1.8 percent yearly income growth. "High" represents 1.6 and 2.6 percent, respectively.

b For supply shifters "low" stands for yearly productivity growth rates lowered by 0.5 percentage points and the additional irrigation area set at 200,000 instead of 270,000 ha. "High" represents productivity growth rates rising by 0.5 percentage points and the irrigation area at 340,000 ha.

Source: Own calculations.

Table 9 .17 shows that under the assumption of higher supply shifters and lower demand shifters the terms of trade effect would be at €81.4 million accruing from fruit and vegetable exports, only because in such a situation no imports of milk products would occur. In case of low supply and high demand shifters, the positive terms of trade effect of fruit and vegetable exports would reduce to about €33 million, and the negative effect resulting from highly priced imports of milk products from the EU would increase to almost €133 million. As a result, the terms of trade effect would amount to about a negative € 100 million.

### **9.3.3 Effects on Welfare Distribution**

### **<IP_ADDRESS> Changes in Producer Surplus per Region**

Table 9.18 shows changes in producer surplus per region. For plant producers, the north central, south central, and the Black Sea regions account for more than 50 percent of welfare losses. In relative terms, losses are highest in the northeast and the Black Sea regions, where losses amount to about 13 percent of the production value. This is mainly due to the high shares of sugar (northeast) and tea (Black Sea) in total plant production. Losses are lowest in the Aegean, Mediterranean, and southeast regions due to the high shares of fruits and vegetables and cotton, for which prices decline only modestly or remain constant. Absolute welfare changes for animal producers are distributed more equally among regions than those for plant producers. In relative terms they vary from 15 percent of production value in the north central region and 24.5 percent in the southeast. Determining factors are discussed above in Section 9.1.3, as the regional distribution of welfare changes is quite similar to that of changes in production value (Table 9.7).

**Table 9.18: Change in Regional Producer Surplus (mill.€ and percent of production value)**

Source: Own calculations.

Under the CU scenario, about 44 percent of losses in producer surplus for plant products occur in the Black Sea region, mainly due to low tea prices. For underlying reasons of regional distribution of welfare changes under the CU scenario, see Section 9.1.3 above.

In order to interpret these results with respect to the effects of different policy scenarios on intrasectoral income distribution, it is necessary to conclude from model results to what extent rich or poor farmers gain or lose under the respective model results. The data base on which such a discussion can be based is limited. Nonetheless, preliminary investigations are carried out below.

A first task is to relate regional welfare changes to the regional farm income level. Unfortunately, no data on farm income per farm household and region is available. It is therefore, unknown whether a region has relatively rich or poor farmers. But if farm size is taken as an indicator for income status, some conclusions can be drawn as regional data on farm size exists from the 1991 agricultural census **(SIS,** 1994 ). However, the basic assumption that farmers on physically large farms are more wealthy than those on small farms is subject to severe limitations. For example the share of irrigated area, the extent of animal husbandry, and the composition of plant production have a strong impact on farm income in addition to farm size. In order to give an impression of regional farm size distribution, Table 9.19 shows shares of small, medium, and large farms in the number of farms and the agricultural area per region.

**Table 9.19: Distribution of Farms by Area and Region, 1991**

Source: SIS (1994); own calculat1ons.

Table 9 .19 shows that in l 991 3 7 percent of Turkish farm land was farmed by 5.4 percent of farmers at farms larger than 20 ha whereas 67 percent of farmers were farming about 22 percent of farm area on farms below 5 ha. The extent of inequality of farm land distribution differed strongly among regions. For example in the Black Sea region farm land was distributed quite equally among the farming population with 86 percent of farmers farming about 55 percent of farm area on farms smaller than 5 ha. Only about 9 percent of farm area belonged to farms larger than 20 ha. In southeast Anatolia, on the other hand, only 6 percent of area belonged to farms smaller than 5 ha, and almost 70 percent of area belonged to farms larger than 20 ha and was farmed by only 17 percent of south east Anatolian farmers. No generalizing statements can be made based on these figures with respect to the effect of agricultural policy

liberalization on intrasectoral income distribution. Regions with relatively equal distribution are subject to high losses of producer surplus (Black Sea, compare Table 9.18) as well as low losses of producer surplus (Aegean region). Regions with relatively unequally distributed area, on the other hand, are subject to low (Mediterranean region) as well as high (north east Anatolia) relative changes in producer surplus.

This approach could be extended to the provincial level. Although provincial welfare changes are not an output of TURK.SIM, the base period production level of products covered by TURK.SIM for all provinces is known (SIS, *Agricultural Structure,* various issues). As changes of producer surplus are known for individual products (see Table 9.12), welfare changes for each province could be estimated roughly based on provincial composition of production. Provincial farm size distribution is also known (SIS, 1994) and welfare changes could thus be related to the distribution of farm size as has been done on a regional level above. This approach is not pursued here.

A second approach for drawing conclusions on intrasectoral income distribution is to relate welfare changes for individual products (Table 9.12) directly to farm size. The information necessary to do so is the distribution of product-specific production with respect to farm size. For plant production, the area allocated to individual plant products per farm size group is published for some products on a national and a regional level **(SIS,** 1994). Unfortunately, the distribution of sugar and tea production, two of the three plant products with the highest contribution to changes in producer surplus under the liberalization scenario, is not published. But for wheat, for which prices decrease considerably under both scenarios, data is available.

Under the assumption that yield does not differ among different farm size groups, Table 9.20 shows the distribution of numbers of wheat producing farms and wheat production, and thus changes of producer surplus, among different farm size groups on a national level and for the southeast Anatolian region. On a national level, 38.4 percent of the change in producer surplus for wheat under the liberalization scenario falls within the farm size group above 20 ha, and is captured by only 7.1 percent offarmers. In a region in which large farms prevail like south east Anatolia even more than 68 percent of the change of producer surplus falls within the farm size group larger than 20 ha and is captured by 18.5 percent of farmers. These results show the well-known fact that agricultural support policies which are coupled to the production level are usually unable to achieve a more equal income distribution pattern, as they increase intra-sectoral inequality in absolute terms.

#### **Table 9.20: Distribution of Changes in Producer Surplus for Wheat among Farm Size Groups (percent)**

• Figures differ from those in Tables 9.19 and 9.21 as only wheat producing fanns are included in the sample.

Source: SIS (1994); own calculations.

For animal production, estimates of the numbers of cattle, as well as sheep and goats per farm size group on a provincial level, are published **(SIS,** 1994). Table 9.21 presents a summary of this data.

**Table 9.21: Distribution of Farms, Area, and Ruminants, by Farm Size and Region, 1991**

Source: SIS (1994); own calculations.

Table 9.21 shows that ruminants are more equally distributed among farm size groups than is farm area. On a national level, for example, 67 percent of farmers account for only 22 percent of farm area, but own 42 percent of national cattle stocks and 54 percent of national sheep and goats. The interpretation with respect to the distribution of welfare effects of changing ruminant product prices is somewhat ambiguous. This is because no information is provided on the herd size per farm. The high share of stocks covered by small farms in terms of area could result from two reasons: many small farms keeping few animals, or a few farms of small size keeping large numbers of ruminants, i.e. feedlots. The incidence of such farms, however, is small in Turkey (USDA GAIN Report TU 1034, 21.08.2001, p.2). The interpretation of Table 9.21 as indicating a more equal distribution of ruminants than farm area among farms is also supported by the fact that only 3 .4 percent of Turkish farms are exclusively engaged in animal production and account for 6.5 percent of the national sheep and goat herd, and 4 percent of the national cattle herd. More than 70 percent of farms are engaged in animal husbandry as well as crop production. These farms account for more than 90 percent of the national ruminant herd **(SIS,** 1994). As a result, price changes for ruminant products still affect large farms most in absolute terms; but as ruminants are more equally distributed among farms than area, this effect is not as distinct as for wheat.

### **<IP_ADDRESS> Change in Consumer Welfare per Income Group**

At the consumption side, welfare changes can be attributed to income quintiles due to the specification of human demand functions for each quintile in TURK.SIM. The change in consumer welfare for each quintile under the liberalization and the CU scenarios compared to the status quo scenario is presented in Table 9.22.

**Table 9.22: Change in Consumer Welfare by Income Quintile**

Source: Own calculations.

Columns 1 and 4 of Table 9.22 show, that the change in consumer welfare under the liberalization and CU scenarios increases in absolute terms with increasing income. This simply reflects the fact that high income groups spend more money on food than low income groups. For example, the change in consumer welfare is more than twice as high in quintile 5 than it is in quintile 1 under the CU scenario. The second column of Table 9.22 shows, that the change in consumer welfare under the liberalization scenario, expressed as a percentage of food expenditure, is almost equal in all quintiles. This is, at a first glance, somewhat surprising as animal product prices decrease significantly more under the liberalization scenario than do plant product prices (see Table 9.2), and animal products cover a higher share of food expenditure in higher income quintiles than in lower ones (Annex Table A-7.3). Under the status quo scenario, expenditures for animal products cover 31 percent of food expenditure in quintile 1, but more than 36 percent of food expenditure in quintile 5. However, this is not the case for all animal products; for milk, which accounts for more than half of expenditures for animal products, the expenditure share is higher in low income quintiles than in higher ones. Also on some plant products, for which prices strongly decline, like wheat and sugar, low income quintiles spend a higher expenditure share than high income quintiles. For instance, the expenditure share for wheat in the base situation is 11.2 percent for quintile 1, and 6.3 percent for quintile 5. Together these effects offset the distributional effect of strongly declining red meat prices which affect higher income quintiles relatively more. Under the CU scenario, high income quintiles are slightly more affected than low ones in terms of percentage of food expenditure (Column 5), which is due to milk prices decreasing only slightly under that scenario.

Columns 3 and 6 of Table 9.22 show that low income quintiles gain relatively more from food price reductions in terms of percentage of total expenditure, as lower income quintiles spend a higher share of their total expenditures on food. For example, under the liberalization scenario, the change in consumer welfare amounts to 2.5 percent of total expenditure for quintile 1 whereas it is only 1.6 percent of total expenditure of quintile 5.

#### **9.4 Impact of Changes in Farmgate-Wholesale Price Margins and the Real Exchange Rate**

As discussed above, increasing competition under the liberalization and CU scenarios could lead to a rise in efficiency of the marketing system (Section 4.1.2). In a situation of perfect competition, such a rise in efficiency would be completely passed on to producers and consumers in the form of a lower marketing margin. 64 The results of such a decrease in margins are presented in Table 9.23.

Source: Own calculations.

Table 9.23 shows that a relatively small reduction of the relative and the absolute components of the processing margin (see Section 5.3) by 10 percent has a significant impact on trade and welfare. Under the liberalization scenario, a decrease of 10 percent of the processing margin leads to a reduction of net imports by €273 million, or 15 percent of total net imports. The positive effect of decreasing margins on producer surplus is €488 million and the change in consumer welfare of decreasing margins is €26 million. Overall welfare effects are €514 million, which is 77 percent of the welfare effects of the liberalization scenario, without any change in margins. If also the share of waste, which contributes to the total margin between farmgate and wholesale price (see above Section 5.3), is reduced by IO percent, trade and welfare effects are even higher; total welfare increases by €745 million under the liberalization scenario.

64 A decrease of the marketing margin coupled with real improvements in technical efficiency, could also result from firms in the marketing chain being forced to pass on part of their producer rent to consumers and farmers. This effect would have mainly distributional rather than allocational effects and is not analyzed in this study.

Turkey is a country with a highly volatile exchange rate and strong inflation. Between the TURK.SIM base period and January 2003 the nominal exchange rate of the Turkish Lira against the Euro increased by more than 1000 percent. Under the TURK.SIM scenarios presented above, the assumption is that the real exchange rate remains constant over the projection period. This, however, is somewhat questionable as the Turkish Lira declined against the Euro by 6.6 percent in real terms between the TURK.SIM base period and January 2003.65 Therefore TURK.SIM is again solved under the assumptions of the real exchange rate increasing by 10 percent and the real exchange rate decreasing by 10 percent over the projection period. Table 9.24 shows results of these calculations. Agricultural prices increase with a real devaluation of the Turkish Lira by 6.1 to 8.9 percent under the different scenarios. The increase of production value is somewhat higher due to increased production quantities. In contrast, with a constant real exchange rate, Turkey is a net exporter of agricultural products under all scenarios. In the case of real appreciation of the Turkish Lira, domestic prices and agricultural production value decrease and Turkey is a net importer of agricultural products under all scenarios.

Welfare effects under both the liberalization and the CU scenarios are somewhat lower in the case of devaluation, and somewhat higher with an appreciation of the Turkish Lira than they are with a constant real exchange rate. This is because prices fall more significantly as a result of liberalization or a CU with appreciation scenario; protection under the status quo scenario is higher. Aggregate welfare results, however, are in the same order of magnitude under differing assumptions with respect to the real exchange rate.

65 The real exchange rate is calculated as the nominal exchange rate multiplied by the EU Harmonised Consumer Price Index (as provided by the EUROPEAN CENTRAL BANK), divided by the Turkish Consumer Price Index (as provided by SIS).

#### **Table 9.24: Effects of Real Devaluation and Appreciation of the Turkish Lira**

Source: Own calculations.

# **10 CONCLUSIONS**

Turkey has liberalized its agricultural markets significantly in recent years. For future policy design, several options exist, three of which are analyzed in the framework of this study. First, the maintenance of the degree of market intervention at the level of 1996/98 is analyzed. This option is somewhat outdated by actual policy developments as Turkey has, under the World Banksupported agricultural policy reform program, lowered protection levels for some products, and intends to continue on this path. Second and third, scenarios of complete agricultural trade liberalization or unilateral agricultural trade liberalization in the CU with the EU are analyzed. It appears that the option of an inclusion of agriculture in the CU with the EU is very similar to the option of complete liberalization of agricultural trade for most products. This is because the EU has, in recent years, significantly liberalized its agricultural markets and is projected to continue to do so for many reasons, including the WTO process, Eastern enlargement, and an interest in further liberalizing trade in the framework of bilateral agreements.

At first, the principal question of whether or not to liberalize the Turkish agricultural sector is discussed because such a liberalization would also be part of the CU option for most products, too. Then, the question as to whether the agricultural sector should be liberalized completely or whether it should be liberalized within a CU with the EU is addressed.

### **10.1 Liberalization of the Agricultural Sector**

The complete liberalization of the agricultural sector leads to significant static comparative welfare gains as shown above. For the year 2006, these welfare gains are estimated at about €670 million or about 2.3 percent of projected agricultural production value, or 0.4 percent of projected GDP. If one adds the assumption that, due to increased competition, marketing margins decrease by 10 percent, welfare gains could even be about €1,400 million. These results have shown to be relatively stable even in the face of variation of critical exogenous parameters like the real exchange rate, the shadow price for sugar, and supply and demand shifters. Other dynamic gains, like enhanced productivity growth rates, are not covered by simulations in the framework of this study.

However, aside from aggregated welfare gains, distributional aspects are important. At the consumption side, the liberalization of the agricultural sector leads to a more equal distribution of real income in relative terms because lower income groups spend a higher share of their income on food and therefore gain relatively more from lower food prices. At the production side, the liberalization of the agricultural sector reduces intrasectoral income inequality in absolute terms, as large and wealthy farms receive most of the gains in producer surplus resulting from current price support due to their high share in production.

One other major distributional effect of liberalization of agricultural policies, however, may conflict with the interests of Turkish policy makers: the distribution from producers to consumers and thus from rural to urban areas. The 1994 income survey shows the mean income in rural areas as 24 percent lower than in urban areas (SIS, 1997). In 1994 the poverty gap in rural areas, indicating the share of total income that has to be transferred to the poor in order to raise all poor to the poverty line, was about 30 percent higher than in urban areas, with the poverty line set at half the median income (Cakmak, 1998).

**TURK.SIM** results overestimate the effect of shifting income from producers to consumers because agricultural producers also act as consumers and do therefore capture part of the loss of producer surplus in the form of the compensating variation at the consumption side. Nonetheless, land owners and agricultural producers of most products clearly lose from liberalization in the comparative static framework of TURK.SIM. Even if one reduces total losses of €2,749 million by one-third due to the share of agricultural producers in total food consumption, the resulting losses of about €1,833 million still account for about 6.4 percent of projected production value in 2006. As about 90 percent of agricultural producers in Turkey operate exclusively on their own land **(SIS,**  1994), and tenancy ofland is oflow significance in Turkey, most of these losses must be borne by farmers and would not be passed on to land owners due to lower land leasing prices.

Various options for poverty reduction measures and measures to support rural areas exist as alternatives to shifting money from taxpayers and consumers mainly to large producers by price supporting policies. Policies aiming better at social and regional development objectives include enhanced public investment in rural infrastructure such as schools, roads, medical care, and so on. People in rural areas benefit from such policies more equally, independent of their farm size or income source. Furthermore productivity in agriculture has the potential to increase significantly through investments in education of farmers, as almost no training opportunities for farmers exist in the current situation. Finally, for the purpose of poverty reduction, direct payments to small farmers are an alternative which is currently implemented under the agricultural policy reform package. Major drawbacks of such payments are the administrative and budgetary requirements. The budget revenue required to finance direct payments could be generated by imposing a low tax on food consumers in order to avoid the possibly negative distributional effects of additional income taxation (see below). If transaction costs of direct payments are not too high, consumers would still be better off with the introduction of such a tax under liberalization because the gross price of food would fall by more than the tax required to finance income transfers to needy groups of producers.

One last distributional effect of liberalizing agricultural markets in Turkey should at least be mentioned. Subsidizing agriculture withdraws resources from other parts of the economy directly by shifting taxpayers' money, and indirectly via the impact on factor markets and the real exchange rate. Therefore, liberalizing the agricultural sector will have positive effects on other sectors of the economy. These general equilibrium effects could indeed generate positive welfare effects significantly larger than those resulting from the partial equilibrium model used in this study.

In terms of policy priorities it seems reasonable for Turkey to first do away with all remains of budget-financed agricultural market policies, such as intervention buying, export subsidies, input subsidies, and producer premiums. This is because, in addition to the negative comparative static negative welfare effects of such measures, budget-financed support is subject to transaction costs in the context of collecting and distributing taxpayers money. Some of these transaction costs are unavoidable, but for Turkey these transaction costs are especially problematic:

" ... the tax system in Turkey is believed to be very inefficient, limited in its coverage, full of leakages and critically depends on the income taxes from fixed income wage and salary earners and indirect taxes collected from consumers. Different estimates show that the size of the untaxed/unrecorded economy in Turkey reaches 30 to 50 per cent of total GNP. It is therefore not too unrealistic to expect that the transfers to agriculture from taxpayers have a relatively larger burden on middle and lower income groups than on higher income groups ... " (Cakmak, 1998, p. 9).

In such a situation the collection of taxes itself probably has a negative effect on income distribution and it is of special importance to limit budgetary outlays to efficient policies well aimed at socially accepted goals.

The second step of liberalizing the agricultural sector after abolition of budgetfinanced market policies would be the reduction of tariffs. Several considerations play a role when thinking about the timing of tariff abolition. Cereals are protected strongly in the current situation. To reduce cereal tariffs at an early stage of the reform process would have two advantages. First, cereals cover a high share of consumption expenditures in low income groups. Price reductions would, therefore, especially relieve the situation of poor consumer groups. Secondly, reductions of cereal prices would increase competitiveness of animal production. An early commitment not to rise domestic price levels for cereals significantly above the international price level could therefore increase the willingness of producers to invest especially in the relatively competitive poultry and egg sectors. Tariff reductions for animal products should be carried out according to a long-term, transparent schedule as animal production often requires long-term investments of farmers and sudden price movements can endanger the ability of farmers to pay off these investments.

Furthermore from an economic point of view, it would make sense to decrease tariffs first for products which are more highly subsidized in order to reduce intrasectoral distortions of the production program. In the area of plant products, this is especially the case for sugar. Welfare effects of a reduced sugar price could be considerable, dependent on the current shadow price for sugar; competitiveness of other products for which Turkey has a comparative advantage in production would increase. Another product for which there is an enormous peak in protection is tea. In that case, however, production is geographically concentrated and limited to the Black Sea region, and producers are highly specialized and generally small-scale farmers. Options for the diversification of agricultural production should therefore be investigated and for a limited period of time tariff protection may be the best solution for the Turkish government to transfer money to tea producers as an alternative to direct payments which have to be financed from the budget.

### **10.2 Extension of the CU with the EU to Cover Agricultural Products**

As discussed above, the degree of liberalization does not differ much between the liberalization and the CU scenarios for most products. The most important price differences are higher prices for sugar, milk, and sheep meat under the CU scenario. The total welfare gain under the customs union scenario is about €200 million lower than under the liberalization scenario. This is mainly due to lower welfare gains for milk, and somewhat less to sheep meat. The welfare difference for sugar is relatively low as the price reduction under the liberalization scenario has little effect on allocation because of the shadow price being significantly below the market price under the status quo scenario, together with a low price elasticity of demand for sugar. Dependent on the assumptions made on the shadow price for sugar in the base situation, the difference in welfare gains for sugar under the liberalization and the CU scenarios could be more significant.

Compared to the status quo and the liberalization scenario, the CU scenario would be equivalent to a "partial liberalization" of the Turkish milk and sheep meat market as prices would be lower than under the status quo scenario, with the resulting "partial welfare gains." Still EU reform of agricultural markets will

proceed, and for milk and sugar, options for further price reductions are currently under discussion.

The pure terms of trade effect of a CU as defined above is surprisingly small. Turkey would gain about €60 million of export revenue because of export prices above world market level for some fruits and vegetables, and would lose about €50 million because of import prices above world market level for milk products. This result, however, is conditional on several assumptions made. First, it depends on the assumptions made about shifters of supply and demand (see Table 9.17). If supply shifters tum out to be higher, or demand shifters tum out to be lower than assumed here, the terms of trade effects would be higher for exported fruits and vegetables and lower for the import product milk.

Secondly, an important assumption made above influencing the terms of trade effect is that the abolition of the entry price system for fruits and vegetables would have no significant impact on Turkish prices due to high transportation cost and highly priced Turkish supply of high quality products (Section 2.2.3). But Turkey's currently disadvantageous geographic location for exports of fresh products to the EU could considerably improve if Central European countries join the EU from 2004 on, and their import demand increases due to increasing income. Central European markets may also be more suitable for somewhat lower qualities at lower prices than north European markets.

Finally it is maintained that the degree of policy harmonization between Turkey and the EU, as potentially " ... required to establish freedom of movement of agricultural products" (Art. 23:1, Customs Union Decision) is, from a purely economic point of view, very limited. As discussed above (Section 4.3.2) all kinds of direct payments, input subsidies, and rural development measures could remain under purely national/EU responsibility. Sugar is projected to be the only product for which Turkey would probably need to apply a supply control system not to exceed 100 percent self-sufficiency.

A problem might arise from the fact that tariff revenue for third country (i.e. non-EU) imports coming into Turkey would still accrue to the Turkish budget. This would be a strong incentive for the Turkish government to promote imports from third countries (rather than from the EU) for those products where the EU price is much above world market level (for example dairy products). This could even lead to a situation where Turkey, being a net importer of the product concerned, would export some of its domestic production to the EU while importing the same product from third countries at a lower price. The most straightforward way to deal with this problem would be to have a common budget with the EU for tariff revenue. An alternative, possibly easier to implement, would be that Turkey's tariff revenue for agricultural products would directly accrue to the EU budget. The EU, on the other hand, could compensate Turkey by a lump sum to be paid each year which would be independent from actual tariff revenue. The incentive for Turkey to import products from third countries for which the EU is a net exporter would thus be removed.

Based on simulations made in this study, it seems that comparative static welfare effects do not clearly favor or disfavor an inclusion of agriculture in the CU with the EU, compared to a unilateral liberalization. The relevance of higher export prices and lower import prices for some products is estimated to be small, if determining factors are varied ( see Table 9 .17). The main difference is that liberalization would be slower for some products in the CU (sheep, sugar, milk) than it could be in the event of reduction of Turkish MFN trade policies.

There are other reasons that could be relevant for Turkey when determining the intensity of its efforts for further liberalization of agricultural trade with the EU. If Turkish policy makers intend to liberalize agricultural markets due to motives of efficiency, budgetary austerity, and income distribution, it may be easier to do so in a CU than on a MFN basis. This is because liberalization may be easier to defend to the Turkish public if it "must be done" because of the CU. The CU could therefore have the same self-binding function for Turkish policymakers as the WTO process has had for many politicians in industrialized countries.

The stabilization of agricultural trade policies because of their long-term binding in a CU could also have positive effects on the disposition for domestic and foreign investments in the Turkish food processing industry. Also, the further harmonization of product and processing standards, which would probably go along with a CU, may enhance this disposition and could result in gains from trade for Turkey as well as for the EU.

It may also be of importance to know how Turkey's position in the negotiating process with the EU on further integration would be influenced by its position with respect to the integration of agricultural markets. In other words, if the EU is interested in agricultural integration, would Turkey's negotiating capital increase with a readiness to remove agricultural trade barriers? Or would Turkey have to pay a political price for the further integration of agricultural markets?

Finally, as Turkish membership draws closer, the integration of agricultural markets would include the possibility of a smooth transition period instead of a sudden adjustment in the event of full membership. This argument, however, is considered premature as full EU membership of Turkey will probably not take place before 2010, and the CAP is a rapidly moving target. Turkey should therefore base its policy on the expected short- to mid-term advantages and disadvantages of a CU in agriculture.

#### **REFERENCES**

AgraEurope (London) Ltd. (2003), *CAP Monitor.*

Paper No. 27, Institute of Agricultural Development in Central and Eastern Europe.

World Bank (2002), *WDI online database.*  http://publications.worldbank.org/ecommerce/catalog/product?item id=631625

World Bank (various issues), *Global Commodity Markets.*

#### **Annex to Chapter 3: Overview of Existing Preferences Granted by the EU for Agricultural Imports Originating in Turkey (as of April 2001),**

#### **CN Chapter 1 - Live Animals**

Source: TARIC, *Official Journal of the European Communities,* C *119 A,* 23.04.2001.

#### **Annex** to **Chapter 3, continued**

#### **CN Chapter 2** -**M** --

0

#### **Annex to Chapter 3, continued**

#### **CNCh 4 -Dairy Products, E** ,I!] s, **H**

#### **CN Chapter 5 - Products of Animal Origin not Elsewhere Specified**

#### **CN Chapter 6 - Live Plants and Fl**

N

#### **CN Chapter 8 - Fruit and Nut**

Harald Grethe - 978-3-631-75692-8 Downloaded from PubFactory at 01/11/2019 02:53:55AM via free access

#### **CN Chapter 9** -**Coffee, Tea, M** --

#### **CN Chapter 10- Cereals**

#### **CN Chapter 11- Products of the Milling Industry**

~ °'

#### **Annex** to **Chapter** 3, **continued**

#### **CNCh 12** -**Oilseed dOI Fruit**

#### **CN Chapter 13 - L G R,--'** . **d other Veeetable S d Extracts**

#### **CN Chapter 14 - Vegetable Plaiting Materials and Vegetable Products not Elsewhere Specified**

#### **Annex to Chapter 3, continued**

#### **CN Chapter 15 -Animal and Ve2etable Fats and Oils**

#### **CNCh 16-P** ti **f Meat, Fish or C Moll ,ther Aquatic Invertebrat,**

#### **CNC** -~- **17-S dS Prod**

t;: 0

#### **Ch 18-C** C **p •reu arattons**

#### **h 9 .fc ls, Fl** s **h or Milk; P ks'Prod**

**CN Chaoter 20** -**Preoarations of Vee:eta b les, Fruit, Nuts or other p arts o f Plants**

#### **CNCh 21 • Miscell Edible P**

#### **CNCh 22-B** s-•--· **dV'**

N VI \;J

#### --~ **F Ind** ... .,.,.. ..... ~ **p !Fodd**

#### **CN Chapter 24** - **Tobacco and Manufactured Tobacco Substitutes**

#### ~ .i:,.

#### **Annex to Chapter 5: TURKSIM GAMS Code**

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       r_f_sup(sc,i,reg)
       r_t_area_reg(sc,reg)
       r_qu _r(sc,pl_q,reg)
       r_share(sc,pl)
                             Regional supply (1000 t)
                             Total area grown to plant products ("pl") per region (1000 ha)
                             Regional area quota
                             Shares of plant products in the newly irrigated area
       al) Regional supply variables used to solve the irrigation problem
       r_area_pre_irr(sc,i) Regional area per crop without any add. irr.  1. 1) Area allocation without sugar quota
        q_ area 1 (pl,reg) Regional area allocation for GAP region
        q_ area2(pl,reg) Regional area allocation for other regions
        1.1.2) Distribution of newly irr. area undersc gt 1 without sugar quota
        q_area_pre_irrl(irr) Regional area per crop without any additional irrigation
        q_share2(irr2) Shares for the distr. of irr. area among plant products based on old sh.
        1.2) Regional area allocation equations in scenarios with sugar quota
        1.2.1) Area allocation in case of binding sugar quota
        q_ area3(pl_ nq,reg) Regional area allocation for GAP region
        q_area4(pl_nq,reg) Regional area allocation for other regions
        q_area5(pl_ q,reg) Determination of regional area for quota products
        1.2.2) Distrib. of newly irr. area under sc gt 1 in case of sugar quota
        q_area_pre_irr2(irr_nq) Reg. area per er. without any add. irr. for nq products
        q_area_pre_irr3(irr_q) Reg. area per er. without any add. irr. for quota prod.
        q_share4(irr2_nq) Shares for distr. of newly irr. ar. among plant prod. based on old shares
        q_share5(pl_q) Shares for distr. of newly irr. ar. among plant prod. based on old shares
        1.2.3) Determination of the sugar shadow price
        q_p _ shadow(pl _ q,reg)
        1.3) Regional supply equations for the distribution of newly irrigated area which apply in
        quota and nonquota scenarios
        1.3.1) Determination of area allocation in case ofno quota (to determine allocation shares)
        q_area_pre_irr_t Total regional area without any additional irrigation
```