Determinants Of Total Factor Productivity Research Articles

Determinants of Total Factor Productivity in India: an Econometric Analysis

Productivity rise as a source of growth has high potential to uplift millions out of poverty. Mitigating the productivity gap can play vital role in helping developing countries to offset with developed countries. In this regard, present study attempts to scrutinize the relationship and significance of various determinants of total factor productivity (TFP) in India for the period 1990–1991 to 2019–2020. To this end, autoregressive distributed lag bounds testing approach has been utilized. The results pinpoint that trade openness and unemployment have a positive impact on total factor productivity. On the other hand, inflation has a negative but insignificant relationship with total factor productivity, both in the short and long run. The results imply that exports need to be diversified, and import of capital goods should be encouraged to enhance TFP in the long run. Further, foreign-owned business entities need to be encouraged to hire domestic workers, which would result in enhanced TFP in the long run.

The Role of Manufacturing and Service Exports in Ethiopia’s Economic Growth Performance

The purpose of this study is to investigate the role of manufacturing and service exports in Ethiopia’s economic growth performance from 1995 until 2018. To accomplish the objective, the study developed two versions of an augmented Solow’s (1956) model. Both versions include manufacturing and service exports as potential determinants of total factor productivity (TFF). However, the first version proxies physical capital accumulation with the investment rate, and the second version uses capital per worker. The autoregressive distributed lag (ARDL) bounds testing results of the first version suggest that there is no long-run relationship among the variables. Moreover, the investment ratio and labour force growth rate variables are statistically insignificant, which contradicts the theoretical predictions of the Solow model. On the other hand, the second version of the Solow model with capital per worker shows evidence of a long-run cointegrating relationship among the variables which support the manufacturing export-led growth hypothesis in Ethiopia, in which manufacturing exports are statistically significant, while service exports are statistically insignificant in the long run. Conversely, the results of the first version show that capital per worker has a positive and significant effect on Ethiopia’s economic growth performance. Overall, the main findings suggest that the Ethiopian government should strengthen current policies that emphasize manufacturing exports and maintain high investment rates in physical capital.

OIL RENTS, INSTITUTIONAL DEVELOPMENT, AND TOTAL FACTOR PRODUCTIVITY

This paper investigates the determinants of total factor productivity (TFP) using a panel data model involving 15 petroleum exporting countries during the period 2008-2019. The econometric evidence, based on the Arellano-Bond generalized method of moments, shows that: 1) education raises TFP, which suggests that highly qualified workers are more able to develop new technologies and absorb existing technologies, 2) oil rents lower TFP, which is consistent with the natural resource curse (NRC) hypothesis and, therefore, with the view that rent-seeking and corruption prevent some oil-rich nations from prospering, and 3) the interaction term involving oil rents and institutional development yields a positive effect on TFP, which means that imposing the rule of law, eradicating corruption and improving regulatory quality can effectively contribute to reversing the negative effect of oil abundance on TFP.

An Analysis of Total Factor Productivity of Rice in Assam

The present study was conducted of estimating the total factor productivity (TFP) growth of rice and its contribution to rice production in Assam and examining the determinants of TFP. The study was carried out for two decades, from 1991-92 to 2010-11, using secondary data, estimated us the Tornqvist Theil index. The input, output, and TFP indices were calculated at a constant price (for 1991-92) of the inputs and outputs to nullify the nominal price effect. Again, the indices were computed for per hectare area and total area under rice in the state to know how efficiently inputs were utilized in both situations. To evaluate the determinants of TFP in Assam, regression was carried out by using Cobb Douglas production function. The study revealed that TFP growth for rice at a constant price was found to be positive in both per hectare area and total area for the study period. Determinants like investment in agriculture and allied activities, expenditure in agricultural research and education, HYV area, rural literacy, irrigation, and cropping intensity were found to have a positive impact on TFP.

Determinants of Total Factor Productivity of Large and Medium-scale Manufacturing Industries in Ethiopia: Time Series Analysis

Determinants of Total Factor Productivity of Large and Medium-scale Manufacturing Industries in Ethiopia: Time Series Analysis

Trends and determinants of total factor productivity in Rice (Oryza sativa) and Wheat (Triticum aestivum)

The study estimates total factor productivity (TFP) in rice (Oryza sativa L.) and wheat (Triticum aestivum L.) which form the mainstay of food security in India. The study period is 25 years from 1991–92 to 2015–16, secondary data from 12 major rice and wheat producing states was collected from Directorate of Economics and Statistics (DES). Results depict declining mean TFP for both rice and wheat in the period II (2002–2015) compared to period I (1991–2001) of study. Major producing states have been facing stagnation in productivity and the results also confirm the proposition that technical efficiency could not catch up with the technical progress in both wheat and rice cultivation. Hence, the results confirm that the TFP change was associated more with technical change than with efficiency change in all the states during both the study periods. Thus, the results conclude that the agricultural development strategy has to pay increased attention towards the factors that could influence the efficiency as well along with the factors that result intechnical progress especially in case of rice and wheat which constitute the Indian food security basket.

Determinants of Total Factor Productivity (TFP) among Sugarcane Farmers in Kwara State of Nigeria

The present research empirically determined the factors influencing total factor productivity (TFP) of sugarcane producers in the Kwara State of Nigeria. Data were obtained from using the 2017-2018 sugarcane cropping season field survey through the administration of a structured questionnaire complemented with an interview schedule on 105 sugarcane farmers selected via multi-stage sampling technique. The collected data were analyzed using the conventional TFP index and censored regression model. From the empirical findings, it was observed that inefficiency in the allocation of working capitals, capital consumption, and health-related challenges decreased the TFP of sugarcane farmers in the studied area. However, the study advised the extension agents to educate farmers to be rational in resource allocation in order to optimize their productivity in sugarcane production. In addition, the study advised farmers to adopt health precautious measures in order not to predispose their family members to tropical diseases and should imbibe savings and investment cultures

Sources of Total Factor Productivity and its Determinants of Paddy Farming in Mullaitivu: A Färe-Primont Index Approach

This study estimates the decompositions of farm-level total factor productivity indices and identifies the impact of household char-acters, farming characteristics, and economic characters on the indices of paddy farming in Mullaitivu district, Sri Lanka. Six villages where the paddy is mostly cultivated in the district were selected as the study area and from each village, 20 farmers were selected randomly. The relevant data related to paddy yield, its inputs, demographic and farming characteristics were gathered through the questionnaire in 2020. The Färe–Primont index and its various productivity components were used to analyze the data in the study. The frequency of efficiency components revealed that nearly 38% of the farmers attained less than 50% in total factor productive efficiency, while only 11% of them attained between 50% - 70% in the sample. Overall, the mean of total factor productivity was found to be 0.629 while the mean of total factor productive efficiency was 0.458showed that 62% and 45% of productivity and efficiency exist among the paddy farmers, respectively. The mean value of output-oriented efficiency was found to be 0.861, revealing that, 86% of total factor productivity can be increased by increasing the technical efficiency of paddy yield in the study. Determinants of total factor productivity and its sources were analyzed using the Tobit model and its results revealed that, total factor productivity, total factor productive efficiency, and input-oriented scale mix efficiency mainly determined by the quality of land, farm income, amount of saving, amount of loan and land ownership. Further, availability of training and farm income were the major drivers of output scale efficiency of paddy farms in the study.

Decomposition of climate-induced productivity growth in Indian agriculture

This paper adopts a stochastic frontier approach to investigate the trend and determinants of total factor productivity (TFP) growth in the agriculture sector of India, using extensive district-level data. The assessment of the production frontier highlights the efficiency aspect of Indian agriculture and contributes to an analysis of those factors that might be directly engaged in the production process. After controlling for the district-specific climatic effect in the production of eighteen major crops, TFP growth is deconstructed into technical progress, technical efficiency change and scale effects. Four weather parameters, average temperature, rainfall, evapotranspiration and windspeed, are defined as exogenous determinants of the technical inefficiency term to analyze the influence of changing climate. Based on the true fixed effect model and maximum likelihood method, the estimated TFP growth averaged 0.688% per year between 1990 and 2015. The relative performance of Indian states apparently differs according to estimated productivity scores. The findings show that changes in technical efficiency account for most TFP growth, whereas differences in scale components account for annual and cross-state productivity growth disparities. The study suggests that region-specific policies are required to enhance agricultural productivity and add to the understanding of the arguments over TFP growth in Indian agriculture.

Literature Review on Determinants of Total Factor Productivity (TFP) at the Firm-Level

The assessment of factors affecting TFP growth at the firm-level has been mentioned by many researchers. This paper reviews the determinants of TFP at the micro level. The determinants of TFP examined in this paper are the following: technology, export activities, foreign direct investment, firm location, managerial ability, firm age, and other factors such as financial constraints, salary, capital structure, resource constraint. This is followed by a review of studies analysing multiple determinants of TFP because productivity has many affecting factors, and these factors often interact and create synergies. Omitting other important factors that affect productivity will result in misleading estimates of the production functions and productivity so several studies have addressed this issue by looking at multiple factors that affect productivity.

Measurement and determinants of total factor productivity: evidence from Indian banking industry

PurposeThe purpose of this study is to measure the level of total factor productivity of the Indian banking sector and to identify both the bank-specific and macroeconomic determinants of the total factor productivity after the global subprime mortgage crisis.Design/methodology/approachThe research sample consists of 61 commercial banks including 21 public sector banks, 18 private sector banks and 22 foreign banks. The annual data is collected from the website of Reserve Bank of India from 2008 to 2019. The authors employed the non-parametric DEA approach to estimate Malmquist total factor productivity index for each bank as well as across different ownership groups. The panel data estimation technique was used to identify the determinants of total factor productivity.FindingsThe results suggested that an increase in the technological shift raised the bank's productivity above the optimal frontier. Among the bank-specific determinants, the bank size and bank diversifications are significantly declining productivity, whereas credit-deposit ratio and return on asset significantly increasing productivity. Among the macro-specific determinants, inflation, growth rate and fiscal deficit ratio negatively affect productivity, whereas capital formation to the GVA ratio boosts the level of productivity.Research limitations/implicationsThe authors have used intermediate method to select the inputs and outputs as per the suitability to the context. However, the disaggregate level such as state and district level analysis can be done using production and value-added approaches to explore the regional variations of the banking performance. Furthermore, the parametric methods such as stochastic frontier analysis can be used to examine banking performance, which the authors left for the future research.Practical implicationsThis study suggested that banks should increase the economies of scale of their total assets and focus on the interest-earning activity. The banks need to proactively operate the business policy by following the changing path of inflation. The banks need to reduce their rate of fiscal-deficit to the GVA with the purpose to boost their level of productivity.Originality/valueThe study provides an important implication for bankers and policymakers in terms of heightening the banking performance during the period of dynamic economic events.

Productivity determinants in the construction sector in emerging country: New evidence from Ecuadorian firms

AbstractThe construction sector is one of the most important sectors for economic development due, among other reasons, to the productive chains that it generates. This paper presents an analysis of the determinants of the total factor productivity (TFP) in the Ecuadorian construction sector during the period 2007–2018. In the first stage, we estimate a production function using the Wooldridge (Economics Letters, 2009, 104, 112–114) estimator to correct the simultaneous determination of inputs and firm unobserved productivity. In the second stage, we analyze the main determinants of TFP. These determinants are classified into four groups: internal, international trade, financial constraints, and external characteristics. Our results suggest that firm age is positively related with TFP but negatively related with TFP growth. Similarly, the fact of being a family firm is negatively related with TFP, but size is positively related with TFP and its growth across the construction subsectors. In addition, we find that access to debt and credit is positively related with productivity, but less‐competitive environment is negatively related with productivity. Finally, our results suggest that TFP and its growth are pro‐cyclical with respect to the gross domestic product. Our results have several managerial implications that are discussed in this article.

Non-parametric decomposition of total factor productivity growth in yam production in North-Central Nigeria

Abstract. Non-parametric analysis of total factor productivity change in yam production in North-Central Nigeria from 1992 to 2016 was carried out with the use of secondary data. The secondary production data of yam for that period were collected from Food and Agriculture Statistical (FAOSTAT) data bank. Malmquist Total Factor Productivity Index (MTFPI) based on Data Envelopment Analysis (DEA), was used to empirically analyse the total factor productivity of the yam, while Tobit regression was used to analyse the determinants of total factor productivity in the study area. The results of the MTFPI analysis reveal that yam contributed 1.4% of technical efficiency change to productivity growth over the period studied. The technological contributions to productivity growth regressed at 1.8%. The study revealed the productivity growth of yam to be 0.2%. Tobit regression result showed credit borrowed, government policy (Agricultural Transformation Agenda – ATA), capital, and labour to have significant and positive relationships with the productivity of the crop at either p≤0.05 or p≤0.001 level of probability, which implies that increase in them led to increase in the crop’s productivity. Capital-labour was statistically significant but negatively related to yam productivity at p≤0.01, which implied that utilization of labour in a greater proportion than capital led to reduction or regress in its productivity growth. The study recommends farmers’ training on farm practices and techniques to increase yam productivity. They should be encouraged to accept improved yam varieties from research institutes, properly allocate the production resources and adopt improved technology to achieve productivity growth in the study area.

Econometric Analysis of Total Factor Productivity in India

This article attempts to investigate the potential relationship and significance of various determinants of Total Factor Productivity (TFP) in India for the 1980–2016 time period. Specifically, this is achieved in two stages. In the first, the standard growth accounting approach is used to measure the changes in TFP. Then, the main model for establishing the determinants of TFP growth is estimated using the autoregressive distributed lag (ARDL) model. Our results suggest that inflation and financial development have a statistically positive impact on TFP. Foreign direct investment, imports, and capital formation are found to have a positive but insignificant impact on the TFP. On the other hand, exports, government size, and natural calamities have a statistically negative impact on TFP. Therefore, in order to accelerate the TFP, governments and policymakers need to design and implement policies to increase financial access to the private sector, while maintaining price stability; exports of high-value products; and increased economic integration in the global economy to benefit from foreign investment flows, which brings in new technology.JEL Classification: O4, O40, O47

On modelling the determinants of total factor productivity in the MENA region: a macro-micro firm-level evidence

Using the World Bank Enterprise Surveys for Middle Eastern and North Africa (MENA) countries, the paper estimates total factor productivity (TFP) and examines its determinants. Our contribution is twofold. First, we provide TFP estimates by country and sector for the MENA region and examine how TFP varies with firm's age, size, export status, formal status and ownership. Second, we combine both micro (firm-level) and macro (nation-level) determinants of TFP to show how macroeconomic policies can affect firms' productivity levels. Our findings show that among the micro determinants, government ownership, foreign capital, female managers, owning a foreign certification, and formal registration of firms are all positively associated with TFP, with competition also exerting a positive impact on firms' productivity. All the macro determinants on the other hand, with the exception of trade openness, display the expected influence on TFP as suggested by the literature. Longer time to enforce contracts, high tax burden and high lending rates all tend to have a significantly negative impact on TFP. Higher tariffs, however, have a surprisingly positive impact on TFP which may emphasise the adverse effect trade openness can have on TFP as a result of the economy's limited ability to absorb the positive spillovers of trade.

Does Social Capital Matter for Total Factor Productivity? Exploratory Evidence from Poland

Two issues connected with sustainable development are analysed in this article: total factor productivity (TFP), which measures the efficiency of transforming physical capital and labour into production, and social capital, which is increasingly considered as a factor of TFP. TFP is sometimes viewed as a measure of sustainability, and its high value indicates an effective way of combining and using limited resources. Social capital, in turn, is a determining factor in the social, economic, and environmental dimensions of development. The subject of this analysis is the impact of social capital on TFP. Social capital generates synergistic effects and creates added value using the existing resources. Therefore, it is legitimate to regard it as one of the determinants of TFP. The role of social capital in sustainable development is theoretically grounded and confirmed by numerous empirical studies. Nevertheless, due to the deep dependence on the context, the mechanisms of the impact of this capital on economic effects are still not fully understood. In this paper, social capital is analysed in the context of the post-transformation economy. This context seems to be interesting for two reasons: the relative weakness of social capital in post-communist countries and extensive nature of development these countries have experienced in recent decades, which together can be a barrier to long-term growth in these economies. The purpose of the paper is to identify and assess the impact of social capital in Poland on TFP in a regional breakdown (Nomenclature of Territorial Units for Statistics II - NUTS II). The research period covers the years 2002–2016 and employs econometric modelling methods. Social capital turns out to be a factor in explaining the level of TFP in Polish regions.

Asymmetries in the euro area and TFP growth: evidence from three major European economies

PurposeIn this paper, the authors study the long-run determinants of total factor productivity (TFP) in three major European economies over the period 1983–2017, namely Germany, France and Italy.Design/methodology/approachThe authors focus on the capital misallocation effects, scale effects and labor misallocation effects. To this end, the authors study how real interest rate shocks, real exchange rate shocks, real wage shocks and changes in labor regulation affected TFP in major European countries over the last decades. The authors employ a theoretical and an empirical model to investigate the issue. The empirical results are obtained using a VAR model for estimation.FindingsA stripped-down model of labor market in open economy with technology progress allows to identify the relevant variables affecting TFP. On the empirical ground, the authors find a positive relationship between TFP and real interest rate in the long run. Importantly, the authors detect a positive relationship between TFP and real exchange rate. Further, the authors show that the TFP can respond positively to a stricter labor market regulation and to a higher real compensation per employee. The results provide support to the idea that TFP has a positive relation with prices in the long run, while it may be biased along the cycle because of price rigidity.Research limitations/implicationsThe present model is stylized and may not capture all of the details of reality. The analysis should be extended to a larger number of countries. Technology progress could be proxied using different variables, as the R&D expenditure or the number of patents. Micro data, for specific sectors and industries, can improve the quality of the empirical investigation.Practical implicationsMainly the authors find that TFP has a positive relationship with price changes in the long run, while it may be biased along the cycle because of price stickiness. Capital misallocation and labor misallocation can negatively affect TFP. Thus, the observed divergences in European TFP can be traced back to the misallocation effects attributable to the decrease of real interest rate and real wages, together with the raising labor flexibility. Mainly, the authors detect a positive long-run relationship between TFP and real exchange rate. This outcome strengthens the supply-side view of the relationship between productivity and real exchange rate.Social implicationsThe authors believe that the present setup can be helpful to reflect critically on the nodes at the core of the productivity slowdown and asymmetries in the eurozone. The aim is to implement renewed policies in order to favor economic growth, convergence and stability in the euro area.Originality/valueThis research addresses the issue of asymmetries among European economies by focusing on the role played by real prices in the long run. Traditionally, the dynamics of TFP have been attributed only to technological components, human capital and knowledge. This work shows that the dynamics of prices such as the real interest rate, the real exchange rate and the real wage can also influence the technological process by pushing the production system toward choices that are not always optimal for economic growth. An interesting result of this research concerns the positive relationship between real exchange rates and TFP in the long term, evidence of an important supply-side effect on the technological process.

Determinants of total factor productivity in Pakistan: a time series analysis using ARDL approach

ABSTRACT This study examines key determinants of total factor productivity (TFP) in Pakistan for the period 1970–2018 using the auto-regressive distributive lag (ARDL) bound testing approach. The study conducts a time series analysis on macro-economic indicators namely foreign direct investment (FDI), trade openness and human capital and aims to identify whether these factors impact significantly on TFP. TFP is a measure of the productive capabilities of factors of production (capital and labour), and is crucial in relation to economic efficiency and economic growth. The study applied an ARDL bound test to analyse the long-run and short-run relationship among the variables, and also a Granger causality test to consider causal relationships between the explanatory variables and TFP. The results suggest that TFP has a long-run relationship with FDI and human capital.

How Heterogeneous Are the Determinants of Total Factor Productivity in Manufacturing Sectors? Panel-Data Evidence from Vietnam

One of the remaining challenges in explaining differences in total factor productivity is heterogeneity between sectors and within a specific sector in terms of labor and capital. This paper employs the generalized method of moments (GMM) to identify factors that affect total factor productivity across 21 manufacturing sectors and to clarify the heterogeneous determinants of total factor productivity within manufacturing sectors for the period 2010–2015. Our estimations show that large firms have significantly greater total factor productivity levels than small firms in some fragmentations of firms in terms of both labor and total capital and in some manufacturing sectors. It is suggested that firm characteristics should be considered by the government in establishing relevant policies for enhancing firm productivity.

On Modeling the Determinants of Total Factor Productivity in the MENA Region: A Macro-Micro Firm-Level Evidence

Using the World Bank Enterprise Surveys for Middle Eastern and North Africa (MENA) countries, the paper estimates total factor productivity (TFP) and examines its determinants. Our contribution is twofold. First, we provide TFP estimates by country and sector for the MENA region and examine how TFP varies with firm's age, size, export status, formal status and ownership. Second, we combine both micro (firm-level) and macro (nation-level) determinants of TFP to show how macroeconomic policies can affect firms' productivity levels. Our findings show that among the micro determinants, government ownership, foreign capital, female managers, owning a foreign certification, and formal registration of firms are all positively associated with TFP, with competition also exerting a positive impact on firms' productivity. All the macro determinants on the other hand, with the exception of trade openness, display the expected influence on TFP as suggested by the literature. Longer time to enforce contracts, high tax burden and high lending rates all tend to have a significantly negative impact on TFP. Higher tariffs, however, have a surprisingly positive impact on TFP which may emphasise the adverse effect trade openness can have on TFP as a result of the economy's limited ability to absorb the positive spillovers of trade.