Unintended Consequences Of Trade Liberalisation on Regional Dietary Pattern in Rural India

Cherry Law

University of Kent

Background

• Nutrition transition in developing countries: the shift of dietary pattern from the one dominated by traditional staples to the one high in animal products and other non-cereal food.

• Trade liberalisation is suggested as one of the possible drivers behind the shift. (Shetty, 2002; Pingali and Khwaja, 2004; Thowand Hawkes, 2009; Kearney, 2010).

• However, there is limited empirical evidence on how trade may have affected food consumption pattern.

Stylized facts of India

• In 1991, the Indian government launched a wave of extensive trade reform. The average effective tariff rate was reduced from around 86% in 1989-90 to about 40% in 1991 (Hasan et al., 2007)

• The Indian diet has shifted from cereals to animal products and other food (Rao, 2000; Shetty, 2002; Deaton and Drèze; 2009).

Indian food consumption pattern

1970 1980 1990 2000Cereals 66.3 65.8 63.4 61.7 Starchy Roots 1.7 1.9 1.7 2.0 Fruits & Vegetables 2.8 3.1 3.1 3.7 Animal Products 4.8 5.8 7.1 7.6 Vegetable Oils 4.8 6.5 6.9 8.2 Sugar & Sweeteners 9.3 9.5 9.2 9.7 Others 10.3 7.4 8.4 7.1 Source: FAOSTAT (Animal products include meat, eggs, milk, animal fats, offals, fish and aquatic products. Others include treenuts, stimulants, alcoholic beverages, spices, oilcrops, pulses and miscellaneous.)

(% of total per capita calorie intake per day)

Distribution of regional average budget share in rural India, 1987 and 1997

01

23

4

De

nsity

.2 .4 .6 .8Budget share

1987 1997

Cereals

02

46

810

De

nsity

0 .1 .2 .3Budget share

1987 1997

Eggs/Fish/Meat

Source: the 43rd and 53rd National Sample Survey data

Research question

Can the difference in consumption of cereals and animal products across Indian rural regions from 1987 to 1997 be attributed to their differential degree of exposure to the trade reform?

Yes. The trade liberalisation in 1991 had a negative impact on cereal consumption but a positive one on the consumption of animal products.

Estimation strategy

Following Topalova (2007), the degree of trade protection faced by rural regions is measured as follow:

• 𝑇𝑛𝑡 : nominal ad valorem tariff faced by industry 𝑛 at time 𝑡.

• 𝑊𝑜𝑟𝑘𝑒𝑟𝑟𝑛,1991 :the number of workers in industry 𝑛 in region 𝑟 in 1991

• 𝑇𝑜𝑡𝑎𝑙 𝑊𝑜𝑟𝑘𝑒𝑟𝑟: total workers in region 𝑟

To address for the bias arisen from the assignment of zero tariff to non-traded industries, 𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 is instrumented by:

• 𝑇𝑜𝑡𝑎𝑙 𝑇𝑊𝑜𝑟𝑘𝑒𝑟𝑟: total workers in traded industries in region 𝑟

𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 = 𝑛𝑊𝑜𝑟𝑘𝑒𝑟𝑟𝑛,1991 ∙ 𝑇𝑛𝑡𝑇𝑜𝑡𝑎𝑙 𝑊𝑜𝑟𝑘𝑒𝑟𝑟,1991

(1)

𝑛𝑠𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 = 𝑛𝑊𝑜𝑟𝑘𝑒𝑟𝑟𝑛,1991 ∙ 𝑇𝑛𝑡𝑇𝑜𝑡𝑎𝑙 𝑇𝑊𝑜𝑟𝑘𝑒𝑟𝑟,1991

(2)

Estimation strategy

The baseline regression:

• 𝑊𝑟𝑡: the average percentage of food expenditure spent on the aggregated food group of region r at time 𝑡.

• 𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 : regional measure of exposure to trade liberalization

• 𝐹𝑃𝐼𝑟𝑡 : regional food price index

• 𝐷𝑟: regional dummies.

• 𝜏𝑡: time fixed effect

𝑊𝑟𝑡 = 𝛼 + 𝛽1𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 + 𝛽2𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 ∙ 𝑙𝑛𝐹𝑃𝐼𝑟𝑡 + 𝛾1𝑙𝑛𝐹𝑃𝐼𝑟𝑡

+𝑑𝑟𝐷𝑟 + 𝜏𝑡 + 𝜀𝑟𝑡(3)

Data

• Food consumption data: 43rd, 45th to 53rd National Sample Survey

• Industrial employment data: 1991 Indian Census

• Agricultural tariffs: Topalova (2010) and World Integrated Trade System

• Manufacturing tariffs: Aghion et al. (2008)

Main resultsTable 4. Trade liberalization and food consumption in rural India

Note: All regressions are estimated with constant, region and time dummies. Tariff is instrumented by non-scaled tariff. Robust standard errors clustered at state-year level are given in parenthesis. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level.

Cereals Eggs/ Fish/ Meat

(1) (2) (3) (4)Tariff 0.279** 0.260* -0.256*** -0.258***

(0.135) (0.152) (0.075) (0.079)Tariff*Ln FPI -0.133** -0.137** 0.110*** 0.116***

(0.058) (0.065) (0.035) (0.037)Ln FPI -0.116*** -0.125*** 0.048*** 0.051***

(0.022) (0.022) (0.013) (0.013)FDI reform 0.166*** -0.064**

(0.036) (0.026)Delicensing 0.020 -0.003

(0.021) (0.009)Observation 821 821 821 821R-squared 0.942 0.944 0.932 0.934

The average tariff cut (14.6 %) is associated with a 1.01 % point increase in the food budget share on EFM and a 0.53 % point decrease in that of cereals (relative to national trend).

Note: All regressions are estimated with constant, region and time dummies and controls for other reforms. Tariff is instrumented by scaled tariff in column 2 to 4. Robust standard errors clustered at state-year level are given in parenthesis. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level

Dependent variable Average budget shareMedian budget

shareLn(Calorie)

Definition of tariffNon-scaled Tarifft

(Hasan et al, 2007)IV-Tarifft-1 IV-Tarifft IV-Tarifft

(1) (2) (3) (4)Panel A: Regional consumption of cereals

Tariff 0.060* 0.224 0.390** 0.356(0.035) (0.150) (0.167) (0.392)

Tariff*Ln FPI -0.032** -0.148** -0.208*** -0.020(0.015) (0.061) (0.072) (0.166)

Ln FPI -0.124*** -0.005 -0.121*** 0.010(0.021) (0.019) (0.022) (0.041)

Observation 821 744 821 821R-squared 0.946 0.937 0.939 0.788

Panel B: Regional consumption of eggs/ fish/ meatTariff -0.059*** -0.132** -0.204*** -1.403

(0.017) (0.062) (0.077) (1.163)Tariff*Ln FPI 0.027*** 0.067*** 0.111*** 0.964*

(0.008) (0.026) (0.035) (0.545)Ln FPI 0.051*** 0.007 0.046*** 0.142

(0.012) (0.009) (0.013) (0.118)

Observation 821 744 821 819R-squared 0.939 0.928 0.935 0.825

Robustness check I

Note: All regressions are estimated with constant, region and time dummies and controls for other reforms. Tariff is instrumented by non-scaled tariff . For column 4, only observations prior to 1992 are used and the difference between regional tariffs, FPI and their interaction from 𝑡 + 6 and 𝑡 + 2 are the regressors. Robust standard errors clustered at state-year level are given in parenthesis. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level

Dependent variable 𝑊𝑟1991 −𝑊𝑟1987 𝑊𝑟𝑡

Definition of tariff IV –(Tariff1997-Tariff1992) IV-(Tarifft+6-Tarifft+2)

(1) (2)

Panel A: Regional consumption of cerealsTariff 0.156 -0.442

(0.840) (0.338)Tariff*Ln FPI 0.461 0.351

(0.899) (0.392)Ln FPI 0.044 -0.019

(0.070) (0.025)

Observation 73 371R-squared 0.098 0.949

Panel B: Regional consumption of eggs/ fish/ meatTariff 0.251 0.137

(0.262) (0.165)Tariff*Ln FPI -0.272 -0.119

(0.322) (0.187)Ln FPI -0.020 -0.003

(0.042) (0.011)

Observation 73 371R-squared 0.061 0.924

Robustness check II – Placebo tests

Mechanism behind the trade-diet link

Trade reform

Income PricesFood taste

Income effect

• Demand for animal products is generally more income elastic than that for cereals (Mittal, 2007 and Kumar et al, 2011).

• To identify the trade impact on income at regional level,

• 𝑙𝑛𝑀𝑃𝐶𝐸𝑟𝑡: logarithm of regional average per capita monthly expenditure

𝑙𝑛𝑀𝑃𝐶𝐸𝑟𝑡 = 𝛼 + 𝛽3𝑡𝑎𝑟𝑖𝑓𝑓𝑟𝑡 + 𝑑𝑟𝐷𝑟 + 𝜏𝑡 + 𝜀𝑟𝑡 (4)

Income effect

Table 7. Trade liberalization and total expenditure in rural India

Note: All regressions are estimated with constant, region and time dummies. MPCNE is the monthly per capita non-food expenditure. Tariff is instrumented by non-scaled tariff. Robust standard errors clustered at state-year level are given in parenthesis. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level.

Log real MPCE Log real MPCNE

(1) (2) (3) (4)

Tariff 0.064 0.033 -0.075 -0.094

(0.192) (0.193) (0.311) (0.315)FDI reform 0.201 0.159

(0.127) (0.202)Delicensing -0.013 -0.085

(0.062) (0.106)

Observations 821 821 821 821

R-squared 0.966 0.966 0.926 0.927

Price effect• Marchand (2012) finds evidence for a positive linkage between the

state-level domestic price of a good and the tariff faced by the corresponding industry in India.

Table 8. Trade liberalization and real food prices in rural India

Note: All regressions are estimated with constant, region and time dummies. Other food includes pulses, vegetables, fruits and milk products. Tariff is instrumented by non-scaled tariff. Robust standard errors clustered at state-year level are given in parenthesis. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level.

Cereals Eggs/Fish/Meat Edible Oils Other food

(1) (2) (3) (4) (5) (6) (7) (8)Tariff -0.006 -0.033 -0.344 -0.394 0.730*** 0.615*** -0.644** -0.718***

(0.138) (0.138) (0.264) (0.262) (0.245) (0.231) (0.261) (0.261)FDI reform 0.144 0.288* 0.698*** 0.390***

(0.100) (0.163) (0.158) (0.138)Delicensing 0.049 0.063 0.073 0.180***

(0.040) (0.066) (0.054) (0.066)

Observations 821 821 821 821 821 821 821 821R-squared 0.978 0.978 0.946 0.947 0.951 0.955 0.965 0.966

Determinants of regional food consumptionTable 9. Determinants of dietary patterns in rural India

Note: Contemporary taste is measured by 𝜃𝑟𝑡, the regional component of the budget share equation which cannot be explained by prices and total food expenditure. Robust standard errors clustered at state-year level are given in parenthesis. All regressions are estimated with constant, region and time dummies.. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level.

Cereals Eggs/ Fish/ Meat(1) (2)

Log real MPCE -0.053*** 0.008***

(0.009) (0.003)Log real price

Cereals 0.071*** -0.027***(0.024) (0.003)

Eggs/ fish/meat -0.028*** 0.005**(0.006) (0.002)

Edible oils 0.025* 0.003(0.013) (0.004)

Other food 0.032*** -0.020***(0.007) (0.003)

Contemporary tasteCereals 0.446***

(0.023)

Eggs/ fish/meat 0.766***(0.028)

Observations 821 821

R-squared 0.976 0.987

Taste effect

• The reduction in tariffs enhances consumers’ access to varieties of food that were not previously available to them (Pingali and Khwaja, 2004).

• The increased interaction with foreign culture through the opening of trade may create a demonstration effect which promotes the adoption of western dietary pattern (James, 1987).

Regional food taste

Following Atkin(2013), the regional taste indicator (𝜃𝑟) is constructed as follow:

• 𝑤𝑖ℎ : share of food expenditure that household 𝑖 spent on food group ℎ

• 𝑃ℎ: logarithm of prices of food groups.

• 𝑚 ∶the monthly per capita food expenditure adjusted by the price index (𝑃𝑟∗).

• 𝑍𝑖: A vector of household characteristics

• 𝐷𝑟: regional dummies

𝑤𝑖ℎ = 𝜃𝑟𝐷𝑟 +

ℎ

𝛾ℎ 𝑙𝑛 𝑃ℎ + 𝛽 𝑙𝑛𝑚𝑖𝑃𝑟∗ + δ𝑍𝑖 + 𝜀𝑖

(5)

Taste effect

Cereals Eggs/ Fish/ Meat

(1) (2) (3) (4)

Tariff 0.051 0.042 -0.113*** -0.105***

(0.124) (0.122) (0.029) (0.029)

FDI reform 0.036 -0.049*

(0.059) (0.027)

Delicensing 0.050 -0.008

(0.037) (0.011)

Observations 821 821 821 821

R-squared 0.994 0.994 0.983 0.984

Table 9. Trade liberalization and regional food tastes in rural India

Note: Contemporary taste is measured by 𝜃𝑟𝑡, the regional component of the budget share equation which cannot be explained by prices and total food expenditure. All regressions are estimated with constant, region and time dummies. Tariff is instrumented by non-scaled tariff. Robust standard errors clustered at state-year level are given in parenthesis. ***Denotes significant at the 1% level, **at 5% level, *at 10 % level.

Summary

• Regions experiencing higher exposure to foreign competition consume relatively less cereals and more animal products.

• Trade liberalisation may have both positive and negative impact on health development in developing countries.

• Apart from income and food prices, food taste is found to be an important channel of transmission between trade reforms and food consumption.