International Transmission of Food Prices and Volatilities: A Panel Analysis

Lee , Hyun-Hoon; Park, Cyn-Young Working Paper International Transmission of Food Prices and Volatilities: A Panel Analysis ADB Economics Working Paper Series, No. 373 Provided in Cooperation with: Asian Development Bank (ADB), Manila Suggested Citation: Lee , Hyun-Hoon; Park, Cyn-Young (2013) : International Transmission of Food Prices and Volatilities: A Panel Analysis, ADB Economics Working Paper Series, No. 373, Asian Development Bank (ADB), Manila, https://hdl.handle.net/11540/2072 This Version is available at: https://hdl.handle.net/10419/109495 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/3.0/igo International Transmission of Food Prices and Volatilities: A Panel Analysis Hyun-Hoon Lee and Cyn-Young Park No. 373 | September 2013 ADB Economics Working Paper Series International Transmission of Food Prices and Volatilities: A Panel Analysis The rise of global food prices and volatilities in recent years has made an understanding of their dynamics and influences more important than ever. High food prices pose a significant challenge in developing countries where food is a key household expense, while volatility may impede production and lead to inefficient agricultural resource allocation. In this paper, Hyun-Hoon Lee and Cyn-Young Park study the global, regional, and national factors behind domestic food price inflation and volatility in Asian countries during 2000–2011. By providing comprehensive comparisons, this paper will help policymakers craft more effective responses to high and volatile food prices. About the Asian Development Bank ADB’s vision is an Asia and Pacific region free of poverty. Its mission is to help its developing member countries reduce poverty and improve the quality of life of their people. Despite the region’s many successes, it remains home to two-thirds of the world’s poor: 1.7 billion people who live on less than $2 a day, with 828 million struggling on less than $1.25 a day. ADB is committed to reducing poverty through inclusive economic growth, environmentally sustainable growth, and regional integration. Based in Manila, ADB is owned by 67 members, including 48 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. Asian Development Bank 6 ADB Avenue, Mandaluyong City 1550 Metro Manila, Philippines www.adb.org/economics Printed on recycled paper Printed in the Philippines ADB Economics Working Paper Series International Transmission of Food Prices and Volatilities: A Panel Analysis Hyun-Hoon Lee and Cyn-Young Park No. 373 September 2013 Hyun-Hoon Lee is a Profesor at Kangwon National University, Republic of Korea. Cyn-Young Park is Assistant Chief Economist, Asian Development Bank. This study was prepared as a background paper for the ADB publication “Food Securities in Asia and the Pacific: Issues and Challenges”, and was presented at the Symposium on Food Security in Asia and the Pacific (University of British Columbia, September 2012) and the Regional Workshop on Food Security and Food Safety under Economic and Environmental Turmoil (Kasetsart University, September 2012). We are grateful to the participants for their comments and to Hyung-suk Byun for his research assistance. Asian Development Bank 6 ADB Avenue, Mandaluyong City 1550 Metro Manila, Philippines www.adb.org © 2013 by Asian Development Bank September 2013 ISSN 1655-5252 Publication Stock No. WPS135992 The views expressed in this paper are those of the author and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent. ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. By making any designation of or reference to a particular territory or geographic area, or by using the term “country” in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area. Note: In this publication, “$” refers to US dollars. The ADB Economics Working Paper Series is a forum for stimulating discussion and eliciting feedback on ongoing and recently completed research and policy studies undertaken by the Asian Development Bank (ADB) staff, consultants, or resource persons. The series deals with key economic and development problems, particularly those facing the Asia and Pacific region; as well as conceptual, analytical, or methodological issues relating to project/program economic analysis, and statistical data and measurement. The series aims to enhance the knowledge on Asia’s development and policy challenges; strengthen analytical rigor and quality of ADB’s country partnership strategies, and its subregional and country operations; and improve the quality and availability of statistical data and development indicators for monitoring development effectiveness. The ADB Economics Working Paper Series is a quick-disseminating, informal publication whose titles could subsequently be revised for publication as articles in professional journals or chapters in books. The series is maintained by the Economics and Research Department. Printed on recycled paper . CONTENTS ABSTRACT v I. INTRODUCTION 1 II. GLOBAL AND NATIONAL FOOD PRICE TRENDS 3 III. MODEL SPECIFICATIONS 12 A. Model Specification for National Food Price Inflation 12 B. Model Specification for National Food Price Volatility 14 IV. RESULTS 15 A. Results for Food Price Inflation 15 B. Results for Food Price Volatilities 21 V. SUMMARY AND POLICY IMPLICATIONS 24 REFERENCES 25 ABSTRACT High and volatile food prices pose a significant policy challenge around the world, and an understanding of the dynamics of food price inflation and volatility is essential in designing appropriate policy responses. Using the panel data for 72 countries from 2000 to 2011, the paper assesses the international transmission of food price inflation and volatilities as well as the effects of various internal and external factors on domestic food price inflation and volatility. The paper offers evidence in support of the international transmission of food price inflation and volatility. Specifically, the paper finds that the domestic food price inflation in Asia is strongly associated with the lagged value of global food price inflation (using the FAO food price index), while volatility spillovers from global to domestic food prices are rather contemporaneous. The paper also finds that both national food price inflation rates and volatilities are strongly associated with both intraand extraregional food price inflation rates and volatilities, respectively. The findings also suggest that higher economic growth rates, greater shares of food in merchandise imports, and smaller increases in the share of food in merchandise imports lead to lower domestic food price inflation. An appreciation of local currency, greater political stability, and higher income level are also found to lower domestic food price inflation. On the other hand, higher economic growth rates lead to lower volatilities of food prices. Keywords: Food price inflation, food price volatility, food price transmission, food security, food policy JEL Classification: E31, N50, N55, Q18, F49 I. INTRODUCTION Global food prices and their volatilities have risen sharply in recent years.1 High and increasing food prices pose a significant policy challenge, particularly in developing countries where the share of food in household expenditure is relatively high (FAO et al. 2011). Volatility is an added concern. The world witnesses larger and more frequent swings in food prices, perhaps owing to the effects of climate change and the volatility of oil prices. The high volatility of food prices and the associated uncertainty may impede the production and investment decisions of food producers, and lead to inefficient resource allocation in agriculture. Noting the importance of food price volatility in policy responses, Kharas (2011) argues, “The crux of the food price challenge is about price volatility, rather than high prices per se.” Roache (2010) also observes, “[V]olatility has made the policy response to changes in food prices more challenging and complicated the investment and consumption decisions of many businesses and consumers.” Understanding the dynamics of both food price inflation and its volatility is essential in designing appropriate policy responses. Byerlee, Jayne, and Myers (2006) note that the country context matters when it comes to food price shock and instability. Food price shock and instability would be a serious concern for the poor in countries where there is only one major staple—for example, rice in much of Asia and in Madagascar, wheat in Pakistan and the Middle East to North Africa, white maize in Eastern and Southern Africa, and sorghum and millet in West Africa’s Sahel. The poor would be even more vulnerable in countries that are net importers of such staple food and that are exposed to world food price shocks. Given the increased frequency and severity of food price shocks in global markets, the transmission of global food prices and their volatilities to local food price inflation and volatility should be of particular interest to policy makers in developing countries. Earlier literature has revealed an incomplete pass-through of global food price shocks to the domestic prices of advanced and emerging economies, with an estimated average passthrough coefficient of about 0.30 for most countries (Ianchovichina, Loening, and Wood 2012; International Monetary Fund [IMF] 2011; and Sharma 2003). Considerable difference exists, however, between advanced and emerging economies. The findings indicate that pass-through tends to be larger in emerging and developing economies than in advanced economies (IMF 2011). There are also differences even among emerging and developing countries. Some studies show that the African markets tend to have rather incomplete transmission compared to other regions. On the other hand, transmission appears relatively more complete among Asian countries. The picture in Latin America is more mixed (Conforti 2004). But Headey and Fan (2008) argue that the interventions of local governments in developing countries often hamper the full transmission of international prices. There is also significant heterogeneity across commodity types. For instance, rice has on average a weaker price pass-through in developing Asia, compared to wheat (Dawe 2008). Using data from 2003 to 2007, Dawe (2008) examines the extent to which increases in international cereal prices have been transmitted to domestic prices in Asian countries. He finds that the international food price transmission was generally incomplete in these countries, as the real appreciation of their currencies against the United States (US) dollar during the sample period neutralized a considerable portion of the global price increases when cereals were imported into domestic markets. Local policies on specific agricultural commodities, particularly rice for these Asian countries, seemed to have further stabilized and shielded domestic prices 1 Gilbert and Morgan (2010), however, find that the recent increase in food price volatility is not out of line with historical volatility, which generally went down in the last 2 decades. 8 І ADB Economics Working Paper Series No. 373 Figure 2a: Food Price Volatilities for Asian Countries (with the FAO Food Price Index) Sources: Authors’ calculations using data from the Food and Agriculture Organization of the United Nations (FAO) and national sources accessed through CEIC (www.ceicdata.com). Figure 2b: Food Price Volatilities for Asian Countries (without the FAO Food Price Index) Sources: Authors’ calculations using data from the Food and Agriculture Organization of the United Nations (FAO) and national sources accessed through CEIC (www.ceicdata.com). International Transmission of Food Prices and Volatilities | 9 Table 3: Average of Food Price Volatilities, 2000–2011 Asia Latin America Sub-Saharan Africa Europe Others People’s Republic of China Hong Kong, China India Indonesia Japan Republic of Korea Lao People’s Democratic Republic Malaysia Nepal Pakistan Philippines Singapore Taipei,China Thailand 3.12 1.22 2.71 3.34 0.95 3.87 0.80 1.99 1.12 1.41 2.10 1.87 3.04 1.72 Argentina Bolivia Brazil Chile Dominican Republic Ecuador El Salvador Guatemala Honduras Jamaica Mexico Panama Paraguay Peru Trinidad and Tobago Venezuela 4.13 2.91 2.75 2.37 4.53 5.24 2.15 2.79 2.36 3.73 1.89 4.45 1.28 1.70 6.40 7.23 Botswana Cote d’Ivoire Kenya Malawi Mauritius Nigeria South Africa 2.88 4.35 6.61 1.11 1.88 1.30 2.10 Austria Belgium Croatia Denmark Finland France Germany Greece Hungary Iceland Ireland Italy Luxembourg Netherlands, The Norway Poland Portugal Slovakia Spain Sweden Switzerland United Kingdom 1.33 1.09 2.08 1.15 1.62 1.06 1.29 2.33 2.75 2.92 1.12 0.82 9.99 1.18 3.50 1.01 1.61 2.31 1.08 0.97 0.76 1.36 Algeria Canada Cyprus Egypt Iran Israel Jordan Malta Morocco New Zealand Saudi Arabia Turkey United States 4.28 1.24 1.86 4.19 9.13 1.74 2.50 2.19 4.07 5.34 0.78 5.55 0.97 Regional average 2.09 Regional average 3.49 Regional average 2.89 Regional average 1.97 Regional average 3.37 World_1 6.19 World_1 6.19 World_1 6.19 World_1 6.19 World_1 6.19 World_2 2.67 World_2 2.67 World_2 2.67 World_2 2.67 World_2 2.67 Notes: 1. World_1 is the world’s food price volatility calculated with the Food and Agriculture Organization of the United Nations (FAO) world food price index. World_2 is the simple average of food price volatilities of all countries included in this study. 2. See page 7 for the calculation of volatilities. Source: Authors’ calculations. Table 4 reports correlation coefficients between national and global food price volatilities during 2000–2011. The results show that national food price volatilities were highly correlated with the contemporaneous volatilities of the FAO Food Price Index and with the national food price volatility average. Among Asian countries, the national food price volatilities in the PRC; Hong Kong, China; India; Malaysia; Pakistan; and Thailand showed relatively strong correlations with global food price volatility. Figure 3 shows the average food price inflation rates for different regions and their increasing co-movements in recent years. The average volatilities of regional food prices, reported in Figure 4, also showed growing co-movements during the period. 10 І ADB Economics Working Paper Series No. 373 Table 4: Correlation between National and Global Food Price Volatilities, 2000–2011 Others World_2 –0.06 0.67 0.16 0.32 0.68 0.89 0.66 0.79 0.72 –0.46 –0.95 –0.35 0.89 0.75 Notes: 1. World_1 is the Food and Agriculture Organization of the United Nations (FAO) world food price index. L.World_1 is a 1-year lag of the FAO world food price index. World_2 is the simple average of national food prices of all countries included in this study. 2. See page 7 for the calculation of volatilities Source: Authors’ calculations. L.World_1 –0.63 0.51 0.57 0.58 –0.32 0.39 0.10 –0.11 0.83 –0.80 0.39 –0.30 0.70 –0.26 World_1 –0.35 0.64 0.34 0.55 0.32 0.83 0.51 0.49 0.90 –0.74 0.84 –0.43 0.96 0.38 A lgeria Canada Cyprus Egyp t Iran Israel Jordan Malta Morocco New Zealand Saudi Arabia Tu r key United States Regional average Europe World_2 0.59 0.43 –0.01 0.83 0.58 0.12 0.24 –0.55 0.71 0.85 0.64 0.41 –0.43 0.70 0.78 0.39 0.91 0.44 0.36 0.65 –0.06 0.92 0.90 World_1 –0.06 –0.23 –0.49 0.19 0.89 0.09 –0.16 –0.75 0.59 0.36 0.72 –0.08 0.77 0.86 0.83 0.84 0.47 0.13 –0.47 0.27 0.55 0.57 0.57 World_1 0.32 0.11 –0.29 0.62 0.80 0.00 0.01 –0.71 0.71 0.76 0.74 0.20 0.64 0.85 0.94 0.53 0.86 0.34 –0.01 0.52 0.11 0.90 0.86 Austria Belgium Croatia Denmark Finland France Germany Greece Hungary Iceland Ireland Italy Luxembourg The Netherlands Norway Poland Portugal Slovakia Spain Sweden Switzerland United Kingdom Regional average Sub-Saharan Africa World_2 0.88 0.18 0.33 0.90 0.35 –0.18 –0.48 0.54 L.World_1 0.22 0.83 0.47 0.67 –0.09 –0.18 0.37 0.90 World_1 0.75 0.53 0.44 0.95 0.29 –0.27 –0.15 0.80 Botswana Cote d’Ivoire Kenya Malawi Mauritius Nigeria South Africa Regional average Latin America World_2 –0.54 0.95 –0.14 0.95 –0.48 –0.44 0.90 0.06 0.94 0.69 0.18 –0.06 0.70 0.81 0.21 0.73 0.40 L.World_1 –0.46 0.58 –0.09 0.37 –0.48 –0.31 0.65 0.41 0.43 –0.06 –0.15 –0.90 0.56 0.55 0.89 0.57 0.34 World_1 –0.57 0.94 –0.12 0.86 –0.47 –0.56 0.94 0.17 0.87 0.52 0.01 –0.36 0.78 0.84 0.54 0.83 0.46 Argentine Bolivia Brazil Chile Dominican Republic Ecuador El Salvador Guatemala Honduras Jamaica Mexico Panama Paraguay Peru Trinidad and Tobago Venezuela Regional average Asia World_2 0.70 0.88 0.69 0.31 –0.46 –0.66 0.61 0.80 –0.07 0.91 0.03 0.24 0.51 0.79 0.93 L.World_1 0.02 0.64 0.88 –0.28 –0.19 –0.55 –0.09 0.48 –0.07 0.52 0.40 0.35 0.00 0.64 0.50 World_1 0.55 0.90 0.90 –0.02 –0.38 –0.68 0.31 0.81 –0.15 0.89 0.23 0.39 0.38 0.84 0.90 People’s Republic of China Hong Kong, China India Indonesia Japan Republic of Korea Lao People’s Democratic Republic Malaysia Nepal Pakistan Philippines Singapore Taipei,China Thailand Regional average International Transmission of Food Prices and Volatilities | 11 Figure 3: Food Price Inflation Rates for Different Regions (%) Sources: Authors’ calculations using data from the Food and Agriculture Organization of the United Nations (FAO) and national sources accessed through CEIC (www.ceicdata.com). Figure 4: Food Price Volatilities for Different Regions Sources: Authors’ calculations using data from the Food and Agriculture Organization of the United Nations (FAO) and national sources accessed through CEIC (www.ceicdata.com). The trend of food price inflation and volatility shows that there may be spillovers from global food price inflation and volatility to national food price inflations and volatilities in recent years, particularly since the late 2000s. In the following sections, we will formally test if and to what extent the international transmission of food price inflation and volatility takes place. Using the annual data from 2000 to 2011, we employ the panel data analysis to assess the 12 І ADB Economics Working Paper Series No. 373 transmission of global food price inflation and volatility to national food price inflations and volatilities. We will also assess if regional differences exist in terms of global food price transmission, by focusing on the Asian region and examining how it is different from other regions such as Latin America, sub-Saharan Africa, and Europe. III. MODEL SPECIFICATIONS We construct a panel data set using the inflation and volatility measures obtained in the previous section as two different dependent variables. A. Model Specification for National Food Price Inflation Explanatory variables are grouped into external and internal (domestic) variables. The equation to be estimated is Cit = β0 + EVit β1 + IVit β2 + εit. (1) where Cit is the annual food price inflation rates, EV is a vector of external variables, IV is a vector of internal variables, and εit is an error term. 1. External variables: To assess the effects of transmission of global and regional food price inflations to individual countries, we construct three separate types of external variables. a. Global food price inflation rates World_C1: Global food price inflation using the FAO Food Price Index. L.World_C1: 1 year lag of global food price inflation using the FAO index. This is to account for the lagging influence of global food commodity prices on the food prices of individual countries, as described in the previous section. World_C2: Average of national food price inflations rates of all countries included in this study. b. Intraregional food price inflation rates The intraregional food price inflation rates for different regions are constructed as the simple average of food price inflation rates of the countries in the same region. It is noted that when calculating this measure for each country, that country’s food price inflation is excluded. Asia_Intra_C: Simple average of food price inflation rates of the countries in Asia. Latin_America_Intra_C: Simple average of food price inflation rates of the countries in Latin America. Sub_Sahara_Intra_C: Simple average of food price inflation rates of the countries in sub-Saharan Africa. Europe_Intra_C: Simple average of food price inflation rates of the countries in Europe. International Transmission of Food Prices and Volatilities | 13 c. Extra-regional food price inflation rates The extra-regional food price inflation rates for different regions are constructed as the simple average of food price inflation rates of all countries located outside the region. Asia_Extra_C: Simple average of food price inflation rates of countries outside Asia. Latin_America_Extra_C: Simple average of food price inflation rates of countries outside Latin America. Sub_Sahara_Extra_C: Simple average of food price inflation rates of countries outside subSaharan Africa. Europe_Extra_C: Simple average of food price inflation rates of countries outside Europe. 2. Internal variables: a. Domestic demand factors GDPPC_C: Difference in log of gross domestic product (GDP) per capita in US dollars. This is to capture the country’s economic conditions in terms of business cycle as well as the income-driven increase in the demand for food. Source: World Bank World Development Indicators (WDI).3 POP_C: Difference in log of population. This is to capture the population-driven increase in the demand for food. Source: World Bank WDI. b. Domestic supply factors FPI_C: Difference in log of food production index. This is to capture the country’s general food production conditions. Source: World Bank WDI. FOOD_IMPORT: Share of food in merchandise imports. This is to assess whether countries with greater dependence on food imports experience higher food price inflation rates. Source: World Bank WDI. FOOD_IMPORT_C: Difference in log of share of food in merchandise imports. This is to assess how high food inflation is associated with a change in food imports as a share of merchandise imports. The causality here may be two ways, as domestic food price increase will induce more imports of foreign food products, which in turn may result in lower prices of domestic food products. A positive sign will indicate that the first causality is stronger, while a negative sign will indicate that the second causality is stronger. XRate_C: Difference in log of exchange rates (LOC/ $). As depreciation of local currency (LOC) against the US dollar will result in higher domestic prices of imported food products in local currency, this variable is expected to carry a positive sign. Source: IMF International Financial Statistics.4 3 See http://data.worldbank.org/data-catalog/world-development-indicators 4 See http://elibrary-data.imf.org/ 14 І ADB Economics Working Paper Series No. 373 c. Overall condition of domestic market M1_C: Money growth rates measured as the difference in log of M1. This is to capture the overall inflation pressure due to the expansion of money supply in the market. Source: IMF International Financial Indicators. L.M1_C: 1 year lag of M1_C. This is to capture the lagged effect of money supply on prices. POL_STABILITY: This is a measure of political stability to capture the institutional quality of the market. This measure is also expected to capture the efficiency and consistency of public policies aimed at reducing the impact of various external and internal sources contributing to food price inflation. Source: World Bank WDI. GDPPC: Log of GDP per capita in US dollars. This is to capture the quality of the market as high-income countries are generally expected to reveal lower growth rates in money supply and higher political stability. This is included here as a control variable. Source: World Bank WDI. B. Model Specification for Food Price Volatility The model for food price volatility is similar to that of national price inflation. The dependent variable is replaced with the food price volatility measured as described in the previous section. Explanatory variables are also grouped in two categories: external variables and internal (domestic) variables. The equation to be estimated is Vit = β0 + EVit β1 + IVit β2 + εit. (2) where Vit is the annual food price volatilities, EV is a vector of external variables, IV is a vector of internal variables, and εit is an error term. 1. External variables: To assess the effects of transmission of global and regional food price inflations and volatilities to individual countries, we construct three separate types of external variables. a. Global food price volatilities World_V1: Global food price volatilities measured as the square root of the sum of the squared percentage changes in the quarterly series of every 3-year moving window, using the FAO Food Price Index. L.World_V1: 1 year lag of World_V1. This is to account for the lagged influence of global food commodity price volatilities on the food price volatilities of individual countries, as described in the previous section. World_V2: Average of national food price volatilities of all countries included in this study. b. Intraregional food price volatilities The intraregional food price volatilities for different regions are constructed as the simple average of food price inflation rates of the countries in the same region. It is noted that when calculating this measure for each country, that country’s food price volatility is excluded. International Transmission of Food Prices and Volatilities | 15 Asia_Intra_V: Simple average of food price volatilities of the countries in Asia. Latin_America_Intra_V: Simple average of food price volatilities of the countries in Latin America. Sub_Sahara_Intra_V: Simple average of food price volatilities of the countries in sub-Saharan Africa. Europe_Intra_V: Simple average of food price volatilities of the countries in Europe. c. Extra-regional food price volatilities The extra-regional food price volatilities for different regions are constructed as the simple average of food price volatilities of all countries located outside the region. Asia_Extra_V: Simple average of food price inflation rates of countries outside Asia. Latin_America_Extra_V: Simple average of food price volatilities of countries outside Latin America. Sub_Sahara_Extra_V: Simple average of food price volatilities of countries outside sub-Saharan Africa. Europe_Extra_V: Simple average of food price volatilities of other countries outside Europe. 2. Internal variables: In the equations for food price volatility, except for one variable, all internal variables are identical to those included in the equations for food price inflations. The exception is XRate_C, difference in log of exchange rates, which is replaced with XRate_V, which is defined below: XRate_V: Volatilities of quarterly series of exchange rates (LOC/ $) in a 3-year moving window. Volatile exchange rates increase the riskiness of returns; hence, there may be a positive transmission of exchange rate volatility to the volatility of food prices. IV. RESULTS A. Results for Food Price Inflation Table 5 reports the estimated results for changes in national food price indices using the fixed-effects model. Column (1) presents the results with both year dummies and country dummies included. Global food price changes are not included here because year dummies account for worldwide fluctuations of business cycles, food prices, and so on. Thus, Column (1) presents the estimated results for the internal factors only in the most comprehensive empirical framework. 16 І ADB Economics Working Paper Series No. 373 Table 5: Determinants of National Food Price Inflation: Benchmark Model (1) (2) (3) (4) (5) Change in FAO world food index (t) –0.019 0.060*** (0.015) (0.019) Change in FAO world food index (t-1) 0.101*** 0.144*** (0.017) (0.021) Change in average of national food prices (t) 0.007*** (0.001) GDP per capita growth rate –0.260** 0.057 –0.151* –0.253*** –0.083 (0.102) (0.086) (0.089) (0.093) (0.083) Population growth rate –0.265 0.322 –0.006 –0.128 –0.007 (0.644) (0.686) (0.661) (0.655) (0.648) Free trade index of Economic Freedom of the World 0.011 0.020*** 0.016** 0.016** 0.015** (0.007) (0.007) (0.007) (0.007) (0.007) Change in Food Production Index –0.003 0.010 0.006 0.015 –0.013 (0.038) (0.040) (0.038) (0.038) (0.037) Share of food imports in merchandise imports –0.006*** –0.007*** –0.005*** –0.005*** –0.005*** (0.002) (0.002) (0.002) (0.002) (0.002) Change in share of food imports in merchandise imports 0.006*** 0.007*** 0.006*** 0.006*** 0.005*** (0.002) (0.002) (0.002) (0.002) (0.002) Change in exchange rate (LOC/ $) 0.108*** 0.117*** 0.087*** 0.096*** 0.089*** (0.017) (0.017) (0.016) (0.016) (0.015) M1 growth rate 0.000 0.000 0.000 0.000 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) M1 growth rate (t-1) 0.000* 0.000 0.000 0.000* 0.000 (0.000) (0.000) (0.000) (0.000) (0.000) Political stability index –0.038*** –0.039*** –0.037*** –0.033*** –0.040*** (0.011) (0.012) (0.011) (0.011) (0.011) Log of GDP per capita 0.081* 0.053* 0.032 0.024 -0.005 (0.046) (0.030) (0.029) (0.029) (0.029) Constant –0.711* –0.486* –0.294 –0.225 0.005 (0.410) (0.279) (0.270) (0.268) (0.272) Year dummies Yes No No No No Country dummies Yes Yes Yes Yes Yes Number of observations 497 497 497 497 497 Number of groups 64 64 64 64 64 R2 0.330 0.212 0.272 0.290 0.300 FAO = Food and Agriculture Organization of the United Nations, GDP = gross domestic product, M1 = money supply, R2 = R-squared. Notes: 1. Numbers in parentheses are standard errors. . 2. ***, **, and * denote 1%, 5%, and 10% level of significance, respectively. Source: Authors’ calculations. International Transmission of Food Prices and Volatilities | 17 Among the demand-side factors, GDP per capita growth rate is found to carry a significant negative coefficient. That is, domestic food price inflation seems to be negatively associated with fast-growing income. This is an interesting finding, as growing incomes in poor countries will likely increase food consumption, contributing to food price inflation. However, given the low income elasticity of food consumption, growing incomes in rich countries would not necessarily increase food consumption, leading to food price inflation. As the panel data includes both developing and industrialized countries, the results seem to suggest that many countries in the sample have already reached the threshold for an additional increase in income not necessarily leading to food price inflation. Among the supply-side factors, a country’s import reliance seems to be negatively associated with food price inflation. That is, countries with a relatively high share of food imports seem to experience less food price inflation. However, countries with greater food share increases in their merchandise imports experience high food price inflation. The results suggest that countries that are more open to global food trade may control food price inflation better. On the other hand, a sudden increase of food imports in the share of total imports, perhaps associated with any disruption in domestic food supply, could stoke food price inflation by exposing the country to highly priced global food markets. The depreciation of local currency against the US dollar (i.e. an increase in the local currency value of $1) is positively associated with domestic food price inflation. We also found that greater political stability and higher GDP per capita are strongly associated with lower food price inflation. Conversely, high money growth rates lead to high food price inflation rates. Columns (2)–(4) report the regression results when global food price inflation rates instead of yearly dummies are used. Column (2) reports the results estimated by including the contemporaneous annual global food price inflation rates using the FAO Food Price Index, while Column (3) reports the estimation results including the lagged value of the global food inflation rates. While the contemporaneous global food price inflation does not affect national food price inflation rates, its lagged value does at the 1% level. Specifically, a 10% increase in world food prices incurs an increase of 1.15% in national food prices after 1 year. When we included both in Column (4), the coefficients for both contemporaneous global food price inflation and its 1-year lagged value become significant. However, the coefficient for the lagged value remains much higher (more than two times larger) than the one for contemporaneous global inflation. On the other hand, Column (5) presents the results using the average value of all national food price inflation rates as the global food price inflation rate. The results generally confirm that there is an emerging tendency that national food price inflation rates move together. Table 6 reports the results incorporating regional dummies for interactions among the countries in the same region. As with Table 5, Columns (1)–(2) are estimation results using contemporaneous and 1-year lagged values of global food price inflation, respectively, based on the FAO Food Price Index. Column (3) employs both. Column (4) shows the results using the average of national food price inflation rates as the global food price inflation rate. 24 І ADB Economics Working Paper Series No. 373 V. SUMMARY AND POLICY IMPLICATIONS The main purpose of this paper is to offer a comprehensive assessment of what influenced national food price inflation and its volatilities during 2000–2011. In particular, this paper examined whether and to what extent the domestic food price inflation and volatilities of Asian countries are influenced by those of the other countries in the region, as well as global food price inflation and volatility. We find that domestic food price inflation is strongly associated with the lagged value of global food price inflation using the FAO Food Price Index. Interestingly, volatility spillovers from global to domestic food prices seemed to be contemporaneous. We also find that movements in both national food price inflation rates and volatilities are strongly associated with those in both intraand extra-regional food price inflation rates and volatilities, respectively. It also seems that the inflation of global food prices affects the national food markets in all regions but with a time lag. This paper finds that global food price shocks affect the domestic food price inflation and volatilities in different countries across different regions in different degrees. This finding may be due to the fact that the present study utilized more current data up to 2011, while earlier studies such as those by Byerlee, Jayne, and Myers (2006); Dawe (2008); and Headey and Fan (2008) used data before the recent (since 2007) spikes of global cereal prices. It is crucial for governments and the international community to understand how to limit the transmission of global food prices and their volatilities to the national markets. Our findings suggest that higher economic growth rates, greater share of food in merchandise imports, smaller increase in share of food in merchandise imports, appreciation of local currency, greater political stability, and higher income level all lead to lower domestic food price inflation. In terms of food price volatility, only economic growth rates matters: countries with higher economic growth rates appear to have lower volatilities of national food prices. REFERENCES Baffes, J., and B. Gardner. 2003. The Transmission of World Commodity Prices to Domestic Markets under Policy Reforms in Developing Countries. Journal of Policy Reform. 6. pp. 159–180. Balcombe, K. 2009. The Nature and Determinants of Volatility in Agricultural Prices: An Empirical Study from 1962-2008. In A. Sarris and J. Morrison eds. The Evolving Structure of World Agricultural Trade. Rome: Food and Agriculture Organization of the United Nations (FAO). Blundell, R., and S. Bond. 1998. Initial Conditions and Moment Restrictions in Dynamic Panel Data Models. Journal of Econometrics. 87 (1). pp. 115–143. Byerlee, D., T. Jayne, and R. Myers. 2006. Managing Food Price Risks and Instability in a Liberalizing Market Environment: Overview and Policy Options. Food Policy. 31 (4). pp. 275–287. Conforti, P. 2004. Price Transmission in Selected Agricultural Markets. FAO Commodity and Trade Policy Research Working Paper No. 7. Rome: FAO. Dawe, D. 2008. Have Recent Increases in International Cereal Prices Been Transmitted to Domestic Economies? The Experience in Seven Large Asian Countries. ESA Working Paper No. 08-03. Rome: Agricultural Development Economics Divisions, FAO. Food and Agriculture Organization of the United Nations (FAO), Statistical Database (http://faostat.fao.org/?lang=en). Food and Agriculture Organization of the United Nations (FAO), International Fund for Agricultural Development (IFAD), International Monetary Fund (IMF), Organisation for Economic Co-operation and Development (OECD), United Nations Conference on Trade and Development (UNCTAD), United Nations World Food Program (WFP), World Bank, World Trade Organization (WTO), International Food Policy Research Institute (IFPRI) and United Nations High-Level Task Force on the Global Food Security Crisis. 2011. Price Volatility in Food and Agricultural Markets: Policy Responses. http://www.oecd.org/tad/agricultural-trade/48152638.pdf Gilbert, C. L., and C. W. Morgan. 2010. Food Price Volatility. Philosophical Transactions of the Royal Society. B 365 (1554). pp. 3023–3034. Headey, D., and S. Fan. 2008. Anatomy of a Crisis: the Causes and Consequences of Surging Food Prices. Agricultural Economics. 39 (s1). pp. 375–391. Hernandez, M. A., R. Ibarra-Ramirez, D. R. Trupkin. 2011. How Far Do Shocks Move Across Borders? Examining Volatility Transmission in Major Agricultural Futures Markets. Banco de México Working Papers No. 2011-15. Mexico City: Banco de México. Ianchovichina, E., J. Loening, and C. Wood. 2012. How Vulnerable are Arab Countries to Global Food Price Shocks? World Bank Policy Research Working Paper Series 6018. Washington, DC: World Bank. 26 І References Imai, K., R. Gaiha, and G. Thapa. 2008. Transmission of World Commodity Prices to Domestic Commodity Prices in India and China. Brooks World Poverty Institute (BWPI) Working Paper No. 45. Manchester: BWPI. International Monetary Fund (IMF). 2011. Target What You Can Hit: Commodity Price Swings and Monetary Policy. World Economic Outlook. September. Washington, DC: IMF. ———. 2012. International Financial Statistics. March Washington, DC: IMF. Keats, S., S. Wiggins, J. Compton, and M. Vigneri. 2010. Food Price Transmission: Rising International Cereals Prices and Domestic Markets. Overseas Development Institute (ODI) Project Briefing No. 48. London: ODI. Kharas, H. 2011. Making Sense of Food Price Volatility. Brookings Institution. http://www .brookings.edu/research/opinions/2011/03/03-food-prices-kharas Minot, N. 2011. Transmission of World Food Price Changes to Markets in sub-Saharan Africa. IFPRI Discussion Paper 1059. Washington, DC: International Food Policy Research Institute (IFPRI). Onour, I., and B. Sergi. 2011. Global Food and Energy Markets: Volatility Transmission and Impulse Response Effects. MPRA Paper No. 34079. Munich Personal RePEc Archive (MPRA). Quiroz, J., and R. Soto. 1995. International Price Signals in Agricultural Markets: Do Governments Care? Mimeo. World Bank. Rapsomanikis, G., D. Hallam, and P. Conforti. 2004. Market Integration and Price Transmission in Selected Food and Cash Crop Markets of Developing Countries: Review and Applications. Commodity Market Review 2003–2004. Rome: FAO. Rapsomanikis, G., and H. Mugera. 2011. Price Transmission and Volatility Spillovers in Food Markets of Developing Countries. In I. Piot-Lepetit and R. M’Barek, eds. Methods to Analyse Agricultural Commodity Price Volatility. New York: Springer. Roache, S. K. 2010. What Explains the Rise in Food Price Volatility? IMF Working Paper WP/10/129. Washington, DC: IMF. Sharma, R. 2003. The Transmission of World Price Signals: the Concept, Issues, and Some Evidence from Asian Cereal Markets. Agricultural Trade and Poverty: Making Policy Analysis Count. Paris: Organisation for Economic Co-operation and Development. Timmer, C. P. 2008. Causes of High Food Prices. ADB Economics Working Paper Series No. 128. Manila: Asian Development Bank. von Ledebur, O., and J. Schmitz. 2009. Corn Price Behavior—Volatility Transmission During the Boom on Futures Markets. Paper presented at the 113th EAAE Seminar “A Resilient European Food Industry and Food Chain in a Challenging World.” Crete, Greece. 3–6 September. International Transmission of Food Prices and Volatilities: A Panel Analysis Hyun-Hoon Lee and Cyn-Young Park No. 373 | September 2013 ADB Economics Working Paper Series International Transmission of Food Prices and Volatilities: A Panel Analysis The rise of global food prices and volatilities in recent years has made an understanding of their dynamics and influences more important than ever. High food prices pose a significant challenge in developing countries where food is a key household expense, while volatility may impede production and lead to inefficient agricultural resource allocation. In this paper, Hyun-Hoon Lee and Cyn-Young Park study the global, regional, and national factors behind domestic food price inflation and volatility in Asian countries during 2000–2011. By providing comprehensive comparisons, this paper will help policymakers craft more effective responses to high and volatile food prices. About the Asian Development Bank ADB’s vision is an Asia and Pacific region free of poverty. Its mission is to help its developing member countries reduce poverty and improve the quality of life of their people. Despite the region’s many successes, it remains home to two-thirds of the world’s poor: 1.7 billion people who live on less than $2 a day, with 828 million struggling on less than $1.25 a day. ADB is committed to reducing poverty through inclusive economic growth, environmentally sustainable growth, and regional integration. Based in Manila, ADB is owned by 67 members, including 48 from the region. Its main instruments for helping its developing member countries are policy dialogue, loans, equity investments, guarantees, grants, and technical assistance. Asian Development Bank 6 ADB Avenue, Mandaluyong City 1550 Metro Manila, Philippines www.adb.org/economics Printed on recycled paper Printed in the Philippines