Aquaculture Productivity Convergence in India: A Spatial Econometric Perspective

This paper provides an illustration of evaluating productivity convergence using spatial econometric modelling framework for the aquaculture sector in India. Productivity has been measured using Total Factor Productivity (TFP). The b- and s-convergence concepts that are used to test the convergence hypothesis have been extended to examine the possible presence of spatial autocorrelation and spatial heterogeneity. The results have confirmed the productivity convergence hypothesis, the presence of spillover effects on TFP growth and the presence of spatial regimes in the TFP convergence process which have policy implications. The paper concludes by providing recommendations for further research.Agricultural and Food Policy,

Fish Supply Projections by Production Environments and Species Types in India

The supply studies on the fisheries sector in India have been addressed at the disaggregated level by production environment and by species groups. These would be more imperative and useful for assessing the fish supply at the national level. The fish supply projections by species groups under different production environments have been obtained to a medium-term horizon, by the year 2015 under various technological scenarios. The study has concluded that the supply response to fish price changes has been stronger under aquaculture than marine environment in India. Price and technology have been reported as the important instruments to induce higher supply. The change in the relative prices of fish species would change the species-mix in the total supply. The fish production has been projected as 4.6-5.5 million tonnes of inland fish and 3.2-3.6 million tonnes of marine fish by the year 2015. More than 60 per cent of the additional fish production will be contributed by aquaculture and mainly by the Indian major carps.Agricultural and Food Policy,

Demand for Fish by Species in India: Three-stage Budgeting Framework

The demand studies for the fish sector are limited by their high degree of aggregation, and the lack of empirical basis for estimating the underlying elasticity of demand. In this study, the three-stage budgeting framework with quadratic almost ideal demand system (QAIDS) model has been used for fish demand analysis by species, using consumer expenditure survey data of India. Income and price elasticities of fish demand have been evaluated at mean level for different economic groups and have been used to project the demand for fish to a medium-term time horizon, by the year 2015. The domestic demand for fish by 2015 has been projected as 6.7-7.7 million tonnes. Aquaculture would hold the key to meet the challenges of future needs. Among species, Indian major carps (IMC) would play a dominating role in meeting the fish demand. Results have shown that the estimated price and income elasticities of demand vary across species and income classes. Fish species have not been found as homogenous commodities for consumers. All the eight fish types included in the study have been found to have positive income elasticity greater than one for all the income levels. Hence, with higher income, fish demand has been projected to increase substantially with change in the species mix. The own-price elasticities by species have been found negative and near to unitary.Agricultural and Food Policy,

A Multistage Budgeting Approach to the Analysis of Demand for Fish: An Application to Inland Areas of Bangladesh

This study was conducted to estimate the elasticities of demand for eight different fish types and four income groups in Bangladesh using year-round data collected from inland areas of the country. It uses a three-stage budgeting framework that estimates a demand function for food in the first stage, a demand function for fish (as a group) in the second stage, and a set of demand functions for fish by type in the third stage using a quadratic extension of the Almost Ideal Demand System (QUAIDS) model. The Heckman procedure was used in stage three to remove the possible bias in the parameter estimates brought about by zero consumption. The magnitude of both price and income elasticities varies across different fish types and income quartile groups, indicating the relevance of estimation specific to fish types and quartiles. Except for assorted small fish, the other seven fish types included in the study were found to have positive income elasticity for all income levels. Assorted small fish is an inferior commodity for the richest quartile of the population.Bangladesh, fish demand elasticities, Inverse Mills Ratio, multi-stage budgeting, quadratic extension to Almost Ideal Demand System (QUAIDS), Demand and Price Analysis, International Development, Public Economics, Research Methods/ Statistical Methods, C3, Q21,

Determinants of regional productivity growth in Europe: an empirical analysis

Discussion on the possibilities for and barriers to income convergence and catch-up growth is at the heart of the debate on European regional economic policy. This study presents an empirical analysis of the determinants of regional productivity growth in Europe, using the most recent Cambridge Econometrics regional database, EU KLEMS growth and productivity accounts and EuroStat R&D data. We apply a reduced-form empirical specification for semi-endogenous productivity growth that allows for differences in steady state income levels and long-run growth rates. Productivity growth in a region depends on its level of human capital, the investments in R&D, and the productivity gap with the technology frontier. Empirical findings show that these factors are interrelated. Apart from a technology gap, absorptive capacity is important to realize catch-up. Both convergence and divergence of productivity across regions are possible. Results show that all considered factors have significant effect on disparity in regional productivity growth, although effects across manufacturing and service sectors are different. The estimated model also features stable dynamic properties in response to an exogenous shock. Keywords: Semi-endogenous Growth, Regional Convergence, International Transfer of Technology, human capital, R&D.

Determinants of regional productivity growth in Europe: an empirical analysis

Discussion on the possibilities for and barriers to income convergence and catch-up growth is at the heart of the debate on European regional economic policy. This study presents an empirical analysis of the determinants of regional productivity growth in Europe, using the most recent Cambridge Econometrics regional database, EU KLEMS growth and productivity accounts and EuroStat R&D data. We apply a reduced-form empirical specification for semi-endogenous productivity growth that allows for differences in steady state income levels and long-run growth rates. Productivity growth in a region depends on its level of human capital, the investments in R&D, and the productivity gap with the technology frontier. Empirical findings show that these factors are interrelated. Apart from a technology gap, absorptive capacity is important to realize catch-up. Both convergence and divergence of productivity across regions are possible. Results show that all considered factors have significant effect on disparity in regional productivity growth, although effects across manufacturing and service sectors are different. The estimated model also features stable dynamic properties in response to an exogenous shock

Determining high potential aquaculture production areas - Analysis of key socio-economic adoption factors

Global aquaculture production increased with an average rate of 10% per year since 1990 and 90% of aquaculture production comes from developing countries thus providing livelihood and income especially to marginal groups who have limited access to resources such as agricultural land and financial capital. Geographical information systems (GIS) based decision support models can facilitate the prioritizing of national research, development and extension strategies and targeting of development assistance for aquaculture because they can provide information to stakeholders as to where and under what conditions certain aquaculture technologies would be feasible. Factors that determine the adoption of aquaculture technologies by farmers include agro-ecological (rainfall, temperature, soil type, slope), socio-economic (land, labor, capital, infrastructure, inputs), and institutional characteristics (extension services, producers’ organizations). While maps can be used to display the agro-ecological factors, many important socioeconomic and institutional variables are not explicitly spatial (such as household land holdings or access to education and credits). To enable the integration of socio-economic variables in GIS models, we suggest a methodology comprising of four stages: (1) identification of key factors for successful adoption of target technologies on the micro-level, (2) development of indicators on the meso-level, (3) generation of geo-referenced meso-level indicator data sets for the target area, and (4) assignment of ranking/weights to the indicators. The paper outlines the conceptual framework applied and highlights some of the inherent methodological challenges. Results of the adoption analysis for aquaculture in Bangladesh and Malawi, representing different levels of aquaculture production intensification, are presented and discussed

Forecasting Rice Yields Based ofMarkov Chain theory

The study explores the application of Markov Chain theory for rice yield forecasting. Yield forecasts are based on the eco-physiological process of rice growth given measurable rice crop characteristics and weather data at intermediate times in the growing season of the rice crop. The ORYZA1 model is used to simulate a database containing rice yields and rice crop conditions at specified times during the growing season. The model was ran on 32 years of historical weather data (1959 - 1990) from the meteorological station at the International Rice Research Institute (IRRI), Los Baños(121 15 E Latitude: 14 11 N Altitude: 21.0m), Laguna, Philippines. As input to the model, the study adopted the parameters on one of the representative yield potential field experiments at IRRI during the 1992 dry season for the IR72 variety planted on a 15x15 m2 plot. Based on the output of ORYZA1, a Markov Chain (matrix of transition probabilities) was constructed to provide forecast distributions of rice yield for various rice condition classes at different rice phenological stages prior to harvest. This Markov Chain can provide several statistics of interests. This ranges from mean, percentile (median) and standard error of the forecasts to probability interval forecasts and predicted probabilities of exceeding (or falling bellow) target yields. The simulated rice yield obtained from ORYZA1 model for 32 years ranged from 8.33 to 10.88 ton ha-1 with an average of 9.57 ton ha-1 and a standard deviation of 0.60 ton ha-1. Forecasted yields from the matrix of transition probabilities ranged from 8.58 to 9.45 ton ha-1 and standard deviations ranging from 0.39 to 0.60 ton ha-1. Results also showed that forecasted yields are more consistent when forecasting starts when the rice plants are more mature

Aquaculture Productivity Convergence in India: A Spatial Econometric Perspective

This paper provides an illustration of evaluating productivity convergence using spatial econometric modelling framework for the aquaculture sector in India. Productivity has been measured using Total Factor Productivity (TFP). The b- and s-convergence concepts that are used to test the convergence hypothesis have been extended to examine the possible presence of spatial autocorrelation and spatial heterogeneity. The results have confirmed the productivity convergence hypothesis, the presence of spillover effects on TFP growth and the presence of spatial regimes in the TFP convergence process which have policy implications. The paper concludes by providing recommendations for further research