Olga Murova

Technical efficiency of US dairy farms and federal government programs

In this article, Technical Efficiency (TE) of dairy farms is estimated and analysed with two methodologies: Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA). Using DEA, the TE scores for different states are determined. Further, logistic regression is applied to TE scores to explain how known technical and policy variables affect a farms probability of being efficient. The second methodology employs SFA to estimate and analyse TE scores. Two federal milk policies are considered in this research: marketing policy and milk income loss policy. Federal milk marketing program has shown a significant and negative impact on TE with both methods. Payments under the milk income loss program have shown a positive significant impact in SFA analysis. Both methodologies produced similar outcomes on regional impacts and on the significance of several considered variables. Categorical representation of some variables in graphs provided some additional insights of their effects on TE.

Public investments, productivity and economic growth: A cross-state study of selected public expenditures in the United States

Purpose The purpose of this paper is to use stochastic frontier analysis (SFA) to estimate the efficiency of public investments and their impact on economic growth in the USA using panel data. Results of the study show highly significant and positive relationships between gross state product (GSP) and expenditures on education, transportation, health, welfare, and public safety (police and fire), and negative but significant relationships between output and employment in health care and public safety services. Inefficiencies in the study are measured using per capita tax revenue and time. Tax revenue has a very minimal positive and significant effect on efficiency, while time inversely relates to efficiency. Design/methodology/approach The present study uses SFA to investigate the efficiency of government expenditures in five service sectors – education, transportation, health, welfare, and public safety (police and fire), using recent data and economic trends. The study hypothesizes that changes in the current levels of expenditures in the public sector have a significant impact on the aggregate economy, as measured by GSP. The study uses GSP as the dependent (output) variable, and government expenditure on the five service sectors as the independent (input) variables. Findings Analysis of efficiency for individual states for all 21 years produced interesting results. Overall, the technical efficiency of the public sector was quite high. The average TE score across all years and all states was 0.878. This suggests that public sector operates at a relatively high efficiency level. Originality/value The current SFA model followed Battese and Coelli approach of estimating efficiency of public sectors in each state of the USA. It allowed estimation of policy impact on the overall efficiency. It was applied to macroeconomic panel data.

Productive Efficiency of Public Expenditures A Cross-state Study

Public productivity, in particular the efficiency of public expenditures, has been a subject of academic and nonacademic debate for a long time. A number of studies have been conducted over the years on the subject using mostly conventional statistical methods such as production functions and occasionally using techniques such as data envelopment analysis (DEA). Most of these studies were conducted at a microlevel using a single decision unit with limited data. This study uses a multistage DEA to analyze public productivity using panel data for all fifty states of the United States over a twenty-one–year period. Based on well-known Farrell’s technical efficiency, the study measures productivity using both constant and variable returns to scale. The results of the study show that there has been a general decrease in efficiency during the study period, with some exceptions, consistent with the growth trend in the national economy.