Impact of share of the Agricultural Sector on Distribution Provincial Constructive Budget: Using spatial Regression

مجله اقتصاد و توسعه کشاورزی

Article 2, Volume 31, Issue 2 - Serial Number 36, July 2017, Pages 136-148   

Document Type: Research Article

DOI: 10.22067/jead2.v31i2.59482

Authors

R. Jamshidi^* ; M. Salimifar; M.T. Ahmadi Shadmehri; M. Ghorbani

Ferdowsi University of Mashhad

Abstract

Introduction: Provincial current and infrastructural budgets are the most important economic tools for public sector and can help to reduce regional inequalities and imbalances in Iran. despite the government's expanded role in Iran's economy, but for various reasons, such as access to oil revenues, certain principles of government in society and so on, the importance of the budget as one of the most important economic and social policy instruments are not known. In other words, due to the privileged position of planning and importance of budget in preparation and implementation of medium-term development programs, Budgeting is ineffective in Iran. Therefore, the process of preparation and implementation of the budget management has become a difficult and complex issue in public sector in the last half-century that imposes to the government. So, budgeting pattern is important for presenting provincial capital assets budgeting in that format.
Method and materials: considering that the way of allocation of funds to various sectors of the country, is related to a spatial relationship between regions, a strategy with the ability to measure local heterogeneity should have been applied. Therefore, in this study, the spatial econometrics method spatial Durbin model with the panel data has been employed. The geographic scope of this study includes all provinces and time scope contains 10 years (2005-2014). In this study, variables of provincial revenues, the share of service, industry, agriculture, and oil in GDP, intermediate consumption in economic activity, inflation rate, unemployment rate, gross domestic product per capita, population and province area as programming variables are used. Besides economic, demographic and geographic variables, political variables such as participation in the presidential election and the percentage of votes to elected president in each province have been added to the budget allocation pattern.
Results: The unit root test results showed that all variable is stationary. Two methods are available for estimate the panel data. The first method is fixed effect model and the second method is random effect model. Results of Hausman test confirm that fixed effect model is better than random effect model. Results indicated that the variables of a share of service, industry, agriculture and oil sectors in GDP and gross domestic product per capita have statistically significant effect on an associated budget in provinces. This results illustrated that government approach in budget allocation is economic and according to the positive effect of these variables on attracting budget (except the share of service sector in GDP) can be stated that government in order to expand the production and greater use of the economic potential of provinces invest in areas where investment will lead to more production and economic development. These findings confirm that provinces with advance agriculture and industry sectors attract more budget in comparison with other provinces. The effects of provincial revenues approved in the law on the budget allocated for infrastructure in the region is significant and positive. The results showed a significant negative effect of inflation rate on the budget allocation. This finding is consistent with economic theory because with an increase in inflation rate or the consumer price index will be reduced economic growth of provinces. In fact, increase in inflation rate has a negative effect on the economic efficiency of each province and this leads to less budget allocated to provinces that have a high inflation rate. Variable of unemployment rate has no significant effect on the budget allocated to the provinces. Budget allocation regardless of the unemployment rate in the region indicates that the process of granting budget is based on efficiency criteria. Because the poor and less developed regions with higher the unemployment rates, less credit is given.
Conclusion: In general, the results indicated that government's approach for allocation of budgets in provinces is economic and based on programs. It is necessary to mention that government's approach to allocation of budgets in provinces is not merely a based program and policy-driven approach also had an impact on the budget allocations to the provinces, but these effects are not for province with a high percentage of votes to elected president. In fact, policy-driven approach to creating political-regional integration is used in the acquisition more votes. In other words, if taking into account indirect effects, it can be concluded that government is used application-driven approach to target provinces and policy-driven approach to neighboring provinces in the allocation of budget.

Keywords

Provincial Budgeting; Spatial Econometrics; regional development policy

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