Drivers of agricultural productivity: Evidence from transforming economies (original) (raw)

Drivers of Agricultural Productivity in Agriculture-Based Economy

Journal for the Advancement of Developing Economies, 2018

Stagnation in agricultural productivity, especially in an economy with fast and persistently growing population, would compromise food security. This study examined the factors influencing agricultural productivity in an agriculture-based economy. The study used a 35-year period (1980 – 2014) panel data focusing on Agricultural Productivity (AP), Real Gross Domestic Product (GDP), Government Agricultural Expenditure (EXP), Agricultural Trade Barrier (ATB), Consumer Price Index (CPI), Farm Machinery (MACH), Fertilizer Consumption (FERT), Human Capital (HCAP) and Irrigation (IRRG). Data were analyzed using Impulse Response Function (IRF) and Panel Least Squares (PLS) regression technique. The IRF revealed that there was a positive and stable response of GDP to shocks in AP in agriculture-based economy. Panel Least Squares revealed that consumer price index (p<0.01), irrigation (p<0.01) and machinery (p<0.01) increased AP in agriculture-based economy. However, FERT decreased (p<0.01) AP in agriculture-based economy. The study concluded that AP will grow in agriculture-based economy with an expansion in irrigation application, farm machinery and appropriate use of fertilizer. Therefore, improved irrigation infrastructure and farm machinery that will enhance smallholder farmer’s capacity for all-season cropping and appropriate application of fertilizer should be encouraged for increased agricultural productivity in agriculture-based economy.

Explaining agricultural productivity growth: an international perspective

Agricultural Economics, 2010

With persistent population growth, a dwindling supply of arable land per capita, and the relatively high income elasticity of demand for food in developing countries, there is a growing need for food supply increases to originate from growth in productivity rather than expansions in inputs. In this paper the authors construct levels of total factor productivity in agriculture for 111 countries covering the years 1970 to 2000. Employing this data in panel and cross-sectional regressions, the authors seek to explain levels and trends in total factor productivity (TFP) in world agriculture, examining the relative roles of environmental and geographical factors, human capital, macroeconomic factors, technological processes resulting from globalization and the Green Revolution, and institutional factors such as measures of land inequality and proxies for urban biases in public and private expenditure. The authors conclude that, in addition to standard explanations of productivity improvements such as human capital, openness and environmental factors, both urban biases and inequality have been major impediments to successful rural development.

Agricultural productivity and its determinants: revisiting international experiences

2000

This paper makes three contributions to the literature on agricultural productivity. First, we provide estimates of growth in agriculture’s total factor productivity (TFP) for a panel of countries using a translog-production function. In contrast to most of the existing literature, the evidence suggests that agricultural TFP growth in developing countries has been positive during the past four decades. Second, the

Agricultural productivity in developing countries

Agricultural Economics, 1998

This paper examines changes in agricultural productivity in 18 developing countries over the period 1961±1985. We use a nonparametric, output-based Malmquist index and a parametric variable coef®cients Cobb±Douglas production function to examine, whether our estimates con®rm results from other studies that have indicated declining agricultural productivity in LDCs. The results con®rm previous ®ndings, indicating that at least half of these countries have experienced productivity declines in agriculture. # 1998 Elsevier Science B.V. All rights reserved.

Explaining Agricultural Productivity Levels and Growth

With persistent population growth, a dwindling supply of arable land per capita, and the relatively high income elasticity of demand for food in developing countries, there is a growing need for food supply increases to originate from growth in productivity rather than expansions in inputs. In this paper the authors construct levels of total factor productivity in agriculture for 111 countries covering the years 1970 to 2000. Employing this data in panel and cross-sectional regressions, the authors seek to explain levels and trends in total factor productivity (TFP) in world agriculture, examining the relative roles of environmental and geographical factors, human capital, macroeconomic factors, technological processes resulting from globalization and the Green Revolution, and institutional factors such as measures of land inequality and proxies for urban biases in public and private expenditure. The authors conclude that, in addition to standard explanations of productivity improvements such as human capital, openness and environmental factors, both urban biases and inequality have been major impediments to successful rural development.

Agricultural productivity gap in developing countries

2017

Labor is substantially less productive in agriculture than that in non-agricultural sectors in poor countries. The gap has tended to increase over time. Conclusions from the existing literature, which mainly trace the factors related to labor market frictions and statistical discrepancies, are inconclusive in explaining the magnitude and pattern of the gap. The phenomenon has remained puzzling. In this work, we intend to show that the unexplained portion of the gap and its trend over time can fully be attributed to differences in capital intensities and relative technical change. In formal framework with two sectors, two factors, and exogenous prices, we show that in equilibrium with constant labor supply agricultural productivity gap is related to relative cross-sector technical change through skill-premium and division of, heterogeneous in skills, labor. Under plausible empirical assumptions and stylized facts, resulting propositions imply that technology imports from abroad stimulate the productivity gap between agriculture and non-agriculture in developing countries. The theory developed is substantiated with two sets of empirical estimations on crosscountry longitudinal data. Results imply that technology imports have positive, statistically significant, and robust impact on the sectoral productivity gaps in developing countries. Key findings reinstate the debate regarding appropriateness of technologies transferred into poor economies and corroborate longstanding views that without technological change traditional agricultural productions deliver decreasing returns at increasing rate. High and increasing productivity disparities in developing countries suggest that proper development policies should be implemented to induce more balance and sustainable development. Particularly, in the short run, policies ought to emphasize on the elimination of barriers to free labor mobility between agriculture and non-agriculture, or equally, rural and urban areas. In the long-run, governments should pay greater attention to technical change in the agricultural productions, whether through domestic development or adoption of appropriate technologies from more advanced countries. Accumulation of human capital in the economy, overall, would make more skilled labor available for both traditional and modern sectors to embrace technical changes more smoothly and consistently.

Determinants of Agricultural Productivity: Empirical Evidence from Pakistan’s Economy

Global Economics Review

This article examines the determinants of the total productivity of the agriculture sector which enhances the total agricultural productivity in Pakistan and analyzes the relations among variables used for the analysis from 1990 - 2017. The application of the auto regressive distributed lag technique ARDL was used to approximate various determinants. The area under cultivation, fertilizer consumption, agriculture credit, and rainfall show a positive effect on agriculture productivity, whereas agriculture employment and pesticide consumption show a positive but statistically insignificant effect on agricultural productivity in the long run. While in the short-run all determinants have a positive and significant effect on total agriculture productivity convergence towards equilibrium is shown by error correction term is 0.829.