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Introduction To The Theory And Practice Of Econometrics

The effect of trade openness on economic growth: Some empirical evidence from emerging market economies

This study empirically examines the impact of climate change on cereal production in selected lower-middle-income countries with a balanced panel dataset spanning 1971-2016. The study uses average annual temperature and rainfall to measure climate change. Besides this, CO2 emissions, cultivated land under cereal production, and rural population are used as the control variables. Second-generation unit root tests, i.e., CIPS and CADF, are used to test the stationarity of the variables. Feasible generalized least square (FGLS) and fully modified ordinary least square (FMOLS) models are used to achieve the objective. Pedroni cointegration test confirms the presence of cointegration between cereal production and climate change variables. The findings show that a rise in the temperature reduces cereal production in lower-middle-income countries. In contrast, rainfall and CO2 emissions have a positive effect on cereal production. For robustness purpose, the Driscoll-Kraay standard regression and dynamic ordinary least square (DOLS) models have also found similar results. Dumitrescu-Hurlin test has found the bidirectional causality of cereal production with temperature and CO2 emissions. Also, unidirectional causality is running from rainfall and rural population to cereal production. The adverse effects of temperature on cereal production are likely to pose severe implications for food security. The paper recommends that governments of the sample countries should research and develop heat-resistant varieties of cereal crops to cope with the adverse effects of temperature on cereal production and ensure food security.

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Impact of climate change on cereal production: evidence from lower-middle-income countries

While climate change is having serious impacts on agriculture and may require ongoing adaptation, short-run threats to global food security are also crucial for developing countries. We use dynamic and asymmetric panel autoregressive distributed lag estimators to investigate how the effects of climate change on agricultural productivity vary depending upon the short run and long run in Asia over the period of 1980-2016. The results confirmed that there is a long-run relationship between agricultural productivity and climate change variables; however, only CO2 emissions could be linked to agricultural productivity in the short run. Moreover, while the direction of this effect is positive for the short run, it turns into negative in the long run confirming that carbon fertilization in the atmosphere can to some extent have a positive effect on agricultural productivity.

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The impact of climate change on agricultural productivity in Asian countries: a heterogeneous panel data approach.

This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.

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Assessing the effect of climate change and financial development on agricultural production in ASEAN-4: The role of renewable energy, institutional quality and human capital as moderators

Assessing the impact of climate change on Indian agriculture: Evidence from major crop yields

The impact of climate change on maize yields and its variability in Telangana, India: A panel approach study

The relationship between exports, imports and economic growth in India has been analysed by a large number of empirical studies in the recent past. However, this paper examines the relationship between exports, imports and economic growth in an unexplored way. The study uses monthly dataset for the first time. Johansen’s Co-integration and Granger causality tests were employed in the empirical analysis, using Augmented Dickey Fuller (ADF) and Dickey Fuller (DF) tests. The present study covers data of 12 years’ period from April 2005 to March 2017. The variables used for the study are of I (1) i.e. first order of difference means that they are stationary at first order difference. The Johansen and Juselius Cointegration test was used to determine the presence of a cointegration vector in the variables. Both the ‘Trace and Max-Eigen’ values specified cointegration at 5 percent level of significance, specifying that the variables have a long run relationship. The results of the Granger causality test show that there is bidirectional causality running between exports and economic growth (IIP) as well as imports and economic growth. Therefore, the study confirms that there is bidirectional causality has been found between exports and economic growth which support export-led growth and growth-led export hypothesis. However, this study finally suggests that both growth as well as export promotion strategy are to be pursued consistently with an emphasis on sustainable and inclusive growth.

Exports, imports and economic growth in India: Evidence from cointegration and causality analysis

This study has examined the effects of climatic factors on mean yields and yield variability of four primary crops (rice, cotton, jowar and groundnut) in Telangana state by applying the Jus...

https://journals.sagepub.com/doi/pdf/10.1177/2321022220923197

Climate Change Effects on the Crop Yield and Its Variability in Telangana, India:

PurposeThis paper aims to evaluate the effects of climate variables on the mean yield and yield variability of major pulse crops in the Telangana state of India.Design/methodology/approachAuthors have estimated the Just and Pope (1978, 1979) production function using panel data at the district level of four major pulses in nine former districts of Telangana for 36 years during 1980–2015. A three-stage feasible generalized least squares estimation procedure has been followed. The mean yield and yield variance functions have been estimated individually for each of these study crops, namely, Bengal gram, green gram, red gram and horse gram.FindingsResults have shown that changes in climatic factors such as rainfall and temperature have significant influences on the mean yield levels and yield variance of pulses. The maximum temperature is observed to have a significant adverse impact on the mean yield of a majority of pulses, and it is also a risk-enhancing factor for a majority of pulses except horse gram. However, the minimum temperature is positively related to the mean yields of the study crops except for Bengal gram, and it is having a risk-reducing impact for a majority of study crops. Rainfall is observed to have a negative impact on the mean yields of all pulses, but it is a risk-enhancing factor for only one crop, i.e. Bengal gram. Thus, rising temperatures and excess rainfall are not favorable to the productivity of pulses in study districts.Research limitations/implicationsThe present study is based on the secondary data at the district level and is considering only one state. Season-wise primary data, including farm-specific characteristics, could have been better. The projected climate change and its impact on the mean yields and yield variance of pulses need to be considered in a future study.Originality/valueAccording to the best of our knowledge, this is the first study to empirically evaluate the impact of climatic variables on the mean yields and yield variability of major pulses in Telangana using a panel data for major pulses and nine districts of 36 years time-series during 1980–2015. The study has given useful policy recommendations.

Raju Guntukula

Papers

Assessing the impact of climate change on Indian agriculture: Evidence from major crop yields

The impact of climate change on maize yields and its variability in Telangana, India: A panel approach study

Exports, imports and economic growth in India: Evidence from cointegration and causality analysis

Climate Change Effects on the Crop Yield and Its Variability in Telangana, India:

How does the yield variability in rainfed crops respond to climate variables? Evidence from pulses yields in Telangana, India