ESTIMATING THE IMPACT OF TRANSACTION COST AND TAXES ON GHANA'S ECONOMYWIDE TECHNICAL EFFICIENCY USING SOCIAL ACCOUNTING MATRIX DATA.

This study focuses on analyzing the technical efficiency of the Ghana economy within an inputoutput model framework using a biased-corrected data envelope analysis technique. The input-output data is from Ghana's 2019 Social Accounting Matrix, a detailed empirical representation of an economy's circular flow between production, income distribution, and expenditure, reflecting input allocation according to the existing production technology. The input-output table from the matrix represents the composition of product-sale destinations (outputs) in rows and the composition of raw materials and gross value-added expenses (inputs) in columns, the variables needed in an economywide productive efficiency analysis. There are two approaches for conducting productivity analysis: parametric analysis using stochastic frontier and nonparametric approach using data envelopment analysis. This study preferred data envelopment analysis that relates feasible input and output combinations based on the available data rather than demanding apriori production or costfunction specification. A biased-corrected data envelopment analysis model was applied, which has the advantage of jointly incorporating inputs, outputs, and exogenous variables that might be a source of inefficiency. Results show that Ghana's Gross Domestic Product was $68,338 million in current US dollars in 2019, and the manufacturing sector was the main driver of Ghana's economy, supplying about 48.2 percent of the domestic goods and services, 45.02 percent of intermediate inputs, and 58.04 percent of exports. The average import tax was 12.38 percent. Transaction costs on the value of domestically produced goods and services and value-added tax were 14.75 percent and 0.93 percent, respectively. The average technical efficiency score was 0.954, implying that the industries in Ghana could decrease their inputs by about 4.6 percent while keeping their output constant. Industries in the livestock, fisheries & forestry, and crop sectors were more technically efficient than those in the manufacturing and service sectors. The most inefficient industries were the information & communication and clothing and footwear industries. Although the impact of transaction costs and taxes on technical efficiency was indeterminate, the average technical efficiency decreased to 0.82 after correction for bias. Therefore, the Ghanaian economy can achieve an 18 percent reduction in input requirements while producing the same output level by reducing transaction costs and implementing optimal tax policies. The study generates critical information for policymakers and development agents in Ghana. It is also replicable for developing countries seeking to identify and scale the impact of fiscal policies on economic growth. [ABSTRACT FROM AUTHOR]