Three essays about the evolution and relation of SAARC countries’ agricultural production

• Κύριος συγγραφέας: Ahammad, Shaikh Mostak
• Άλλοι συγγραφείς: Κοντογεώργος, Αχιλλέας
• Μορφή: Thesis
• Γλώσσα: English
• Έκδοση: 2016
• Θέματα: SAARC; Agricultural production; Transmission; Volatility; Αγροτική παραγωγή; Μετακύλιση; Μεταβλητότητα; 630.954

This dissertation presents three essays about the evolution and relation of SAARC countries’ agricultural production. Essay 1 (discussed in Chapter 2) examines the evolution of agricultural production in three SAARC countries: Bangladesh, India and Pakistan. The selection of these countries is based on their agricultural economic importance to the region, as they represent about 80% of the agricultural economy. The unobserved components model is used to decompose the per capita agricultural production of each country, and investigate the relationship of each component among these countries. The time period for the study is 1961–2010, and the FAO’s statistical data set is used. The smooth trend plus stochastic cycle methodology of Koopman et al. (2009) are used to estimate the model by maximum likelihood. The empirical results clearly demonstrate that India is positively correlated with Bangladesh in irregular components, but moderately correlated with Pakistan in growth. Finally, there is evidence of a stronger correlation between the three countries in short cycles than in long cycles. Essay 2 (discussed in Chapter 3) comprises two sections, in which section 3.1 investigates the short-term and long-term relationships as well as regime-switching behavior across the per capita agricultural production of Bangladesh, India and Pakistan, using vector error correction model (VECM) and Markov-switching VECM model (MS-VECM). This section used the same data set which is used in Essay 1. The empirical results confirm the existence of two long-term cointegrating vectors between the variables under consideration and demonstrate that an unexpected shock to the respective log per capita agricultural production of India and Pakistan causes transitory impacts. On the other hand, an unexpected shock to the log per capita agricultural production of Bangladesh causes a permanent disequilibrium in all variables. Finally, MS-VECM model has shown two volatility regimes (i.e. low and high volatility). The Markov-switching impulse responses have indicated that: (i) agricultural production adjustments in the first regime are smoother than those in the second regime, and (ii) these adjustments are faster in the case of a shock to the agricultural production of Pakistan than to the agricultural production of either Bangladesh or India. Section 3.2 investigates the dynamics of cross-country per capita agricultural production growth and volatility spillovers between Bangladesh, India, and Pakistan. This section uses per capita agricultural production data for the period from 1961 to 2012, obtained from the FAO’s statistical database, to construct and estimate a multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) model. The MGARCH model is estimated utilizing the maximum likelihood method. The volatility impulse response functions (VIRF) are also applied to quantify the effects of independent shocks on expected conditional volatility. The model provides good statistical fit and the empirical results indicate significant cross-country per capita agricultural production volatility spillovers among these countries. Essay 3 (discussed in Chapter 4) comprises three sections. Since it is overwhelming recognized that energy is an important factor for the development of economic growth, this chapter examines the interaction between energy consumption and economic growth. In particular, section 4.1 examines the dynamic relationship between energy consumption and the three major sectoral outputs (agricultural, manufacturing and service) in 13 south and south-east Asian countries (i.e. Bangladesh, India, Nepal, Pakistan, Sri Lanka, Indonesia, Malaysia, the Philippines, Thailand, Singapore, Brunei Darussalam, Myanmar and Vietnam) using a panel data framework for the period 1971–2012. Besides, SAARC and ASEAN countries were selected since they are geographical neighbors. It undertakes panel cointegration analysis to investigate the long-run relationship between the variables. In addition, the panel vector error correction model (VECM) and impulse response functions (IRFs) are employed to examine the short- and long-run direction of causality and the effect of responses between energy consumption and the three sectoral outputs. The empirical results reveal that the long-run equilibrium relationship between energy consumption and the three sectoral outputs is positive and statistically significant, indicating the existence of long-run co-movement among the variables. The short- and long-run causality results support the existence of bidirectional causality between energy consumption and the three sectoral outputs, with the exception of the short-run causality between energy consumption and service sector output, which is unidirectional, running from service sector output to energy consumption. The IRFs show that the shocks of all the variables reach the equilibrium level within three to seven years from the initial shock. Sections 4.2 and 4.3 investigate the dynamic relationships between energy consumption and economic growth in nine south and south-east Asian countries (i.e. Bangladesh, Brunei Darussalam, India, Indonesia, Malaysia, Pakistan, the Philippines, Sri Lanka, and Thailand) using a panel data framework. The period for the study is 1990–2012, and the World Bank Development Indicators data set is used. Since the unit root tests evidenced mixed results, this dissertation uses both panel vector autoregression (VAR) and panel vector error correction model (VECM) methods to investigate the relationship between the variables. In addition, Granger causality tests and impulse response functions (IRFs) are employed to examine the direction of causality and the effect of responses between the variables. The panel cointegration analysis reveals that the long-run equilibrium relationship between real gross domestic product, energy consumption, real fixed capital formation and the total labor force are positive and statistically significant, indicating the existence of long-run co-movement among the variables. The panel Granger causality results evidence bidirectional causality effects between energy consumption and economic growth, which supports the feedback hypothesis, meaning that these variables have strong interdependency. The short- and long-run causality results (derived from the panel VECM) support the growth hypothesis in which unidirectional causality runs from energy consumption to economic growth, meaning that the economy of these countries is energy dependent. The IRFs show that the shocks of all the variables require a long period to reach the equilibrium level and the greatest response of each variable is attributed to its own shock.