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Impact of R&d Expenditures, Rainfall and Temperature Variations in Agricultural Productivity: Empirical Evidence from Bangladesh

Ruhul Salim
School of Economics & Finance, Curtin Business School, Curtin University, Perth, WA 6845, Australia

Kamrul Hassan
Department of Finance, School of Management and Governance Murdoch University, 90 South St. Perth, WA 6150, Australia

Sanzidur Rahman
Faculty of Economics, Shandong University of Finance and Economics, Jinan – 250001, China. and Development Consultant (Freelance), Newton Abbot, Devon, TQ12 2BA, UK.

Abstract/ Executive Summary:

This study aims to investigate dynamic relationships between research and development (R&D) expenditure, climate change (measured by annual rainfall and temperature variations), human capital (proxied by literacy) and total factor productivity (TFP) growth in Bangladesh agriculture. Pesaran’s Pooled Mean Group (PMG) estimator is used to a unique panel data of 17 regions of Bangladesh covering a 61-year period (1948-2008). In addition, the panel vector autoregression (PVAR) model is also applied to trace the responsiveness of TFP from a shock to R&D, extension services, and literacy rate. Results reveal that R&D has an insignificant impact on TFP in the short run, while it has a significant positive impact in the long run. The contributions of climate variables (i.e., rainfall and temperature variations) are highly significant and negative in the long run. The literacy rate is found to have a significant positive impact on TFP as expected. These results suggest that agricultural R&D investment and human capital could play an important role to ameliorate the adverse effects of climate change in the agricultural sector of Bangladesh.

Keywords: Climate change, R&D investment, Agricultural productivity growth, Panel data, Co-integration, Bangladesh

Location: In Bangladesh

Start Date:

End Date:

Program Area: Risk Management in Agriculture

Non-commodity: Climate change

Objectives:

To investigate dynamic relationships between research and development (R&D) expenditure, climate change (measured by annual rainfall and temperature variations), human capital (proxied by literacy) and total factor productivity (TFP) growth in Bangladesh agriculture.

Methodology:

Description of data: Various sources are used to construct the database needed for this study. Data on the Bangladesh agricultural sector are taken from the special issue of the Statistical Yearbook of Bangladesh covering the period 1948-1972 (BBS, 1975), and various issues of the annual Statistical Yearbook of Bangladesh covering the period 1975 to 2008 (BBS, various issues). Other data types used in the study (agricultural TFP index, R&D investment, human capital, and climate change) are sourced from a recent study conducted by Rahman and Salim (2013). The database used in this study covers the period 1948–2008, which may seem to be slightly dated. But choosing a cut-off point of 2008 as the terminal year for the analysis is largely dictated by the availability of important variables needed for this study as well as the scale of additional funding and other resource requirements to update the database. For example, data on animal power and labour are from agricultural censuses and the last one was done in 2008. Although a new agricultural census is being undertaken in 2018/19, but the data is not published yet. Similarly, fertilizer information is not available in the BBS yearbooks since 1992. Therefore, additional funding is required to assign researchers to collect and record fertilizer distribution information from several sources by physically visiting institutions to compile and record them. Furthermore, there are no significant changes in terms of the structure of Bangladesh agriculture including farming practices, policies and operating institutions. For example, rice acre remained dominant with very little variation over the past decade. The proportion of rice area declined by only 1.43 per cent from 61.24 per cent in 2008 to 59.81 per cent in 2018 (BBS, 2009; BBS, 2019). Also, there were no major policy changes except the fertilizer subsidy was reintroduced in 2006. Additionally, change in climate in Bangladesh is relatively mild. There are no sharp changes in temperature and/or rainfall. For example, average minimum temperature was 21.7°C and average maximum temperature was 30.5°C in 2008 and the corresponding figures are 21.1°C and 30.7°C in 2018 which represents a decline of 2.76 per cent in minimum temperature and an increase of only 0.66 per cent in maximum temperature over a 10 year period (BBS, 2009; BBS, 2019) . Similarly, the annual total rainfall in Bangladesh was 2099 mm in 2008 and 2059 mm in 2018, a decline of only 1.91 percent in 10 years (BBS, 2008; BBS, 2019). Therefore, we strongly believe that our results are still capable of providing valuable and relevant information for the policymakers, development agencies, the farming community as well as other stakeholders. Empirical modeling: Generally, the economic theory of production provides the analytical framework for most empirical research on productivity (Jorgenson and Griliches 1967; Nishimizu and Page 1982). Theory of production postulates a well-defined relationship between a vector of maximum producible outputs and a vector of inputs. If the production function is corrected for measurement error, the growth in TFP is largely explained by growth in inputs in the production process (Jorgenson and Griliches 1967). This study uses a time series analytical framework by incorporating R&D, rainfall, variations in temperature, agricultural extension services and literacy rate in order to estimate the long-run relationship between these variables and agricultural TFP in Bangladesh. This intermediate estimator allows intercept and short-run coefficients (including error-correction term) to vary across cross-section units; however, restricts the long-run coefficients to be identical across all cross-section units. If the restriction of long-run coefficients homogeneity holds valid, PMG (Pooled mean group) approach yields more efficient estimator than MG. Pesaran et al (1999) propose a Hausman-type test with the null hypothesis of long-run coefficient homogeneity. If the test fails to reject the null hypothesis, the PMG estimator is preferred to MG estimator.

Source of Information: https://pearl.plymouth.ac.uk

Article Link (Online Journal): http://hdl.handle.net/10026.1/1597

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

This study examines the impact of R&D investment on agricultural TFP in Bangladesh based on a unique panel data of 17 regions covering the 61-year period (1948–2008). Other control variables include agricultural extension services, rainfall, temperature variations (growing degrees month), and literacy rate. We employ the panel counterpart of the ARDL model, known as pooled mean group (PMG) estimator to estimate the long-run relationship among the variables of interest. In addition, we also employ the panel vector autoregression (PVAR) model to trace the responsiveness of total factor productivity from a shock to R&D, extension services, and literacy rate. The empirical results indicate that there are long-run equilibrium relationships between agricultural TFP and R&D, and other control variables. Any temporary deviation from this long-run relationship is corrected in less than two years’ time as indicated by the error correction coefficient of 0.51. In the long run, R&D has a positive and significant impact on TFP. The estimated positive effect of R&D might contribute to the estimated technological progress, which grew at a rate of 0.74 percent per annum (Rahman and Salim, 2013). In addition, the panel vector autoregression (PVAR) model is also applied to trace the responsiveness of TFP from a shock to R&D, extension services, and literacy rate. Results reveal that R&D has an insignificant impact on TFP in the short run, while it has a significant positive impact in the long run. The contributions of climate variables (i.e., rainfall and temperature variations) are highly significant and negative in the long run. The literacy rate is found to have a significant positive impact on TFP as expected. These results suggest that agricultural R&D investment and human capital could play an important role to ameliorate the adverse effects of climate change in the agricultural sector of Bangladesh.

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