Hicks Moorsteen Research Articles

Statistical inference for Hicks–Moorsteen productivity indices

AbstractThe statistical framework for the Malmquist productivity index (MPI) is now well-developed and emphasizes the importance of developing such a framework for its alternatives. In this paper, we try to fill this gap in the literature for another popular measure, known as the Hicks–Moorsteen productivity index (HMPI). Unlike MPI, the HMPI has a total factor productivity interpretation in the sense of measuring productivity as the ratio of aggregated outputs to aggregated inputs and has other useful advantages over MPI. In this work, we develop a novel framework for statistical inference for HMPI in various contexts: when its components are known or when they are replaced with non-parametric envelopment estimators. This will be done for a particular firm’s HMPI as well as for the simple mean (unweighted) HMPI and the aggregate (weighted) HMPI. Our results further enrich the recent theoretical developments of nonparametric envelopment estimators for the various efficiency and productivity measures. We also examine the performance of these theoretical results for both the unweighted and weighted mean of HMPI for a finite sample, using Monte-Carlo simulations and also provide an empirical illustration along with the computation code.

Multiple directions for measuring biased technical change

The technological change component of the Malmquist productivity index is defined as the radial distance between isoquants along a single direction. Therefore, it relies on limited information to measure technological change, which is a naturally global phenomenon. This becomes problematic, particularly when technological change is not Hicks-neutral but biased towards certain inputs or outputs. To mitigate this problem, I propose a more global measure of technological change that uses two directions. When combined with existing measures of other contributing factors, this measure constitutes an alternative productivity index, which is the geometric mean of the Malmquist and Hicks–Moorsteen productivity indices based on the cone technologies.

Analysing determinate components of an approximated Luenberger–Hicks–Moorsteen productivity indicator: An application to German dairy‐processing firms

AbstractThe Luenberger–Hicks–Moorsteen (LHM) total factor productivity (TFP) indicator has sound theoretical properties, but its decomposition yields indeterminate components of technical change and scale efficiency change that can become infeasible. The current paper decomposes the approximating Bennet indicator, which results in determinate components of technical change, technical efficiency change, scale efficiency change and mix efficiency change that are always feasible. The application focuses on the German dairy‐processing sector, an important postfarm supply chain actor. We compute 558 growth rates for the period 2011–2020. The results show that the LHM‐approximating Bennet indicator decreases by on average 1.14% p.a., with substantial annual fluctuations. The underlying components of output‐ and input‐oriented technical change also fluctuate substantially, and often conflict. Moreover, output‐ and input‐oriented TFP efficiency change fluctuate moderately on average, which is mainly driven by scale efficiency change and mix efficiency change. The components of technical efficiency change remain relatively stable on average. Indeterminateness is a relevant problem when decomposing the original LHM indicator for the current sample: depending on the specification, the proportion of infeasibilities when decomposing the original LHM indicator ranges between 6.09% and 15.95%. Our proposed determinate decomposition is thus a valuable complement. [EconLit Citations: D24, D25, Q13].

Environmental productivity assessment: An illustration with the Ecuadorian oil industry

AbstractThis paper assesses the performance of 20 Ecuadorian petroleum industry over the period 2014–2018, using the pollution‐adjusted Malmquist (PM) and Hicks–Moorsteen (PHM) productivity indices within a convex neutral analytical framework. Indeed, to the best of our knowledge, the environmental performance variation of the Ecuadorian oil industry has never been investigated hitherto in the literature. Moreover, the existing literature that analyses the environmental performance change of oil industries applied the Malmquist productivity index by considering a convex production set. However, the convexity assumption results in ignoring possible non‐linearities in the production process. Also, the performed PM and PHM in this paper are decomposed and disaggregated to provide the main drivers of both economic and polluting productivity change. Finally, the performance change assessment is carried out through a nonparametric enumerative method that is defined in the paper.

Comparing green productivity under convex and nonconvex technologies: Which is a robust approach consistent with energy structure?

AbstractTotal factor productivity is used to explore the input–output efficiency of the economy and the driving factors behind economic growth. Although scholars have researched the total factor productivity approach, comparisons among different models in empirical research are rare and few scholars have focused on worldwide total factor productivity gains. Using convex and nonconvex technologies, this contribution investigates green productivity gains of 129 worldwide countries during 2000–2019 based on three popular productivity measures, namely, Luenberger–Hicks–Moorsteen indicator, Luenberger productivity indicator, and Malmquist–Luenberger index, respectively. Inspired by a metafrontier approach, we compare their productivity evolutions with the energy structure among 121 economies. A negative relationship is expected between the change in the proportion of fossil fuel energy consumption and green productivity. Our results show that the Luenberger–Hicks–Moorsteen productivity indicator under nonconvex technologies is a more convincing productivity measure when considering undesirable outputs in production technology.

An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities

An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities

Comparing Malmquist and Hicks–Moorsteen productivity changes in China’s high-tech industries: exploring convexity implications

Comparing Malmquist and Hicks–Moorsteen productivity changes in China’s high-tech industries: exploring convexity implications

The digital economy, spatial spillovers and forestry green total factor productivity

Improving forestry green total factor productivity is important for promoting green and high-quality development of the forestry industry. Meanwhile, there are major expectations that the digital economy, which is the new engine driving China's economic development, will help achieve the green transformation and high-quality development of the industry. We systematically examine the impact of the digital economy on forestry green total factor productivity in dynamic and spatial dimensions using a dynamic panel model, mediating effect model and dynamic spatial Durbin model based on the Non-Radial Directional Distance Function-Luenberger Hicks Moorsteen model; furthermore, we measure forestry green total factor productivity in 30 provinces in China from 2013 to 2019. Our results indicate that China's forestry green total factor productivity grew at an average annual rate of 5.03% from 2013 to 2019, maintaining an overall stable growth trend, and the growth rate declined in the order of Central, Eastern, Western, and Northeastern China. At the same time, the positive spatial correlation of green total factor productivity in China's forestry industry increased significantly during this period, and the local spatial correlation showed a trend of gradually shifting to the H–H agglomeration feature, with significant path-dependent characteristics and overall spatial spillover effects. The digital economy can significantly promote an improvement in forestry green total factor productivity, and this conclusion is still valid after robustness tests and endogeneity treatment. The analysis of the mechanism of action shows that industrial structure upgrading and green technology innovation are important mechanisms through which the digital economy can improve forestry green total factor productivity. The heterogeneity analysis shows that the enhancement effect of the digital economy on forestry green total factor productivity is more obvious in the eastern and northeastern regions than in the central and western regions. Finally, according to spatial spillover analysis, the positive effects of the digital economy can have spatial spillover effects on neighboring regions that are geographically close and have similar economies. The research in this paper advances the understanding of the growth drivers of forestry green total factor productivity, the mechanisms, and the regional differences in forestry green total factor productivity as affected by the digital economy.

Energy productivity and greenhouse gas emission intensity in Dutch dairy farms: A Hicks–Moorsteen by‐production approach under non‐convexity and convexity with equivalence results

AbstractThe agricultural sector is currently confronted with the challenge to reduce greenhouse gas (GHG) emissions, whilst maintaining or increasing production. Energy‐saving technologies are often proposed as a partial solution, but the evidence on their ability to reduce GHG emissions remains mixed. Production economics provides methodological tools to analyse the nexus of agricultural production, energy use and GHG emissions. Convexity is predominantly maintained in agricultural production economics, despite various theoretical and empirical reasons to question it. Employing non‐convex and convex frontier frameworks, this contribution evaluates energy productivity change (the ratio of aggregate output change to energy use change) and GHG emission intensity change (the ratio of GHG emission change to polluting input change) using Hicks‐Moorsteen productivity formulations. We consider GHG emissions as by‐products of the production process by using a multi‐equation model. Given our empirical specification, non‐convex and convex Hicks‐Moorsteen indices can coincide under certain circumstances, which leads to a series of theoretical equivalence results. The empirical application focuses on 1,510 observations of Dutch dairy farms for the period of 2010–2019. The results show a positive association between energy productivity change and GHG emission intensity change, which calls into question the potential of on‐farm, energy‐efficiency‐increasing measures to reduce GHG emission intensity.

The Illustrative Understanding on the Informal Sector and Its Influence in Firm Productivity in Sub-Saharan Africa (SSA): Evidence from Cameroon

As globalization continues, textiles and clothing firms have many opportunities around the world. Using survey data, we evaluate the determinativeness of the informal sector and its impact on firm productivity by applying the Hicks–Moorsteen index and Data Employment Analysis (DEA) methods. Specifically, this study estimates factors driving total factor productivity (TFP) and its constituents for Cameroon’s companies from 2005 to 2014. As a result, the input levels of informal textile companies are the significant drivers of TFP with a mean in productivity of 47.06% for textile and 56.69% for clothing (I). Regarding formal textile companies, technical efficiency and technological progress fluctuate throughout the period of study (II). Firm size, technology adoption and primary resources (raw material) are important stages of a firm’s decision to innovate (III). Therefore, employing this approach could be reliable in analyzing firm productivity in other SSA countries.

INFERENCE IN DYNAMIC, NONPARAMETRIC MODELS OF PRODUCTION: CENTRAL LIMIT THEOREMS FOR MALMQUIST INDICES

The Malmquist index gives a measure of productivity in dynamic settings and has been widely applied in empirical work. The index is typically estimated using envelopment estimators, particularly data envelopment analysis (DEA) estimators. Until now, inference about productivity change measured by Malmquist indices has been problematic, including both inference regarding productivity change experienced by particular firms as well as mean productivity change. This paper establishes properties of a DEA-type estimator of distance to the conical hull of a variable returns to scale production frontier. In addition, properties of DEA estimators of Malmquist indices for individual producers are derived as well as properties of geometric means of these estimators. The latter requires new central limit theorem results, extending the work of Kneip, Simar, and Wilson (2015, Econometric Theory 31, 394–422). Simulation results are provided to give applied researchers an idea of how well inference may work in practice in finite samples. Our results extend easily to other productivity indices, including the Luenberger and Hicks–Moorsteen indices.

Analysis of Environmental Total Factor Productivity Evolution in European Agricultural Sector

ABSTRACTProductivity analysis has been an important avenue for economic research. Therefore, medleys of quantitative techniques have been proposed to operationalize productivity analysis. In this article, an extended by‐production model is discussed and applied to ensure a link between the production and the pollution‐generating subtechnologies. The corresponding dual formulations are provided to interpret the economic role of pollution‐generating inputs in the subtechnologies. Finally, we integrate the proposed model with the environmental Luenberger–Hicks–Moorsteen productivity indicator based upon input and output directional distance functions. The proposed model is applied to measure the green economic growth of agricultural sectors of the selected European countries.

Metafrontier productivity indices: Questioning the common convexification strategy

While the construction of metafrontiers based on the union of underlying group frontiers normally yields a non-convex metaset, a large majority in the literature seems to assume that a convexification strategy leads to a reasonable convex approximation of this non-convex metafrontier. However, Kerstens, O’Donnell, and Van de Woestyne (2019) recently deliver new results on the union operator on technologies under a variety of assumptions and empirically illustrate that such a convexification strategy is doubtful. The purpose of this contribution is to verify to which extent such a convexification strategy is tenable when computing the Malmquist and Hicks–Moorsteen productivity indices with respect to a metafrontier. Furthermore, the differences between the Malmquist and Hicks–Moorsteen productivity indices are investigated at the metafrontier level. This existing methodology is empirically applied on a secondary data under a wide variety of assumptions: we explore balanced and unbalanced data as well as constant and variable returns to scale. Anticipating our key results, we provide statistical evidence on the potential bias arising from applying the convexification strategy for the metafrontier productivity indices.

Financial and social efficiency in the Yemen microfinance institutions

PurposeThe purpose of this paper is to discover the most important productivity determinants of Yemeni microfinance institutions. In addition, this study tests the most appropriate tool to measure productivity in such unique industry.Design/methodology/approachThe authors applied data envelopment analysis (DEA) with the variable return to scale after testing the technology return to scale assumption. Then, they used DEA with bootstrapping technique to overcome the borne biasness in the conventional DEA analysis. Finally, the authors presented the Hicks–Moorsteen (total factor productivity [TFP]) as the most suitable tool for the technology presented in this study.FindingsIn this paper, the authors found a prolonged deterioration in the productivity scores of microfinance institutions in Yemen. This study highlights the importance of operating in rural areas to improve micro finance institutions’ (MFIs’) productivity. In contrast, they found no significant differences in productivity, neither between microfinance banks and non-governmental organizations nor between Islamic and non-Islamic MFIs.Research limitations/implicationsThis study extends previous research in the area of productivity and its determinants. It also adds to the body of productivity knowledge and methodology within the context of the microfinance industry in Yemen.Originality/valueThe study discovered new productivity determinants and re-assessed the importance of some already known ones. These determinants have been studied for the first time in Yemen’s microfinance industry and have contributed to answer the question of what is the most suitable productivity method that should be used. This study proved that the Hicks–Moorsteen TFP and the variable return to scale assumption are the only suitable methods to study productivity in the microfinance industry.

A new decomposition and interpretation of Hicks-Moorsteen productivity index for analysis of Stock Exchange companies: Case study on pharmaceutical industry

This paper deals with the productivity index based on Hicks-Moorsteen (HM) productivity index for analysis of Stock Exchange firms. In this paper, a decomposition of Hicks-Moorsteen productivity index is provided that uses data envelopment analysis (DEA) models. On the other hand, it is offered a new interpretation and decomposition for components of HM productivity index that in previous studies were not performed any interpretation of it. These components have named the output production and the input consumption in terms of changing the efficiency frontier. In addition, by comparing the components of HM productivity index and productivity value, the optimal values of output production and input consumption are determined. Also, the analysis is determined how to identify the optimal value of a firm over a period of time. The proposed approach is applied to 26 pharmaceutical manufacturers that are from Tehran Stock Exchange. Data have been collected for six consecutive years (2009–2014) and have been considered financial ratios for evaluating companies. The results show that the Hicks-Moorsteen productivity index is more able to provide managerial aspects than other productivity indexes such as the Malmquist productivity index.

Economies of scope in Portuguese local government using an augmented Hicks–Moorsteen approach

ABSTRACTWhereas a substantial empirical literature has investigated scale economies in local government, by contrast little effort has been directed at economies of scope. To address this gap in the literature, this paper empirically examines economies of scope in 308 Portuguese local governments and the extent to which it explains differential council performance. We employ a new methodology using geometric distance functions, an augmented Hicks–Moorsteen index, and partial frontiers for (in)efficiency assessment in local government. The results demonstrate that most councils that ‘externalize’ service provision face diseconomies of scope, which increase in proportion to the externalization of service provision.

Rent-seeking in agricultural policy revisited: a new look at the Common Agricultural Policy consensus

It is generally believed that agricultural interventionism represents the payment of political rents to farmers. We attempt to show that the concept of political rent known as the rent-seeking theory is not valid for agricultural policy. It is not justified to identify the entire subsidies paid to agriculture as a ‘political rent’, since political rents cannot be taken to include payments for the supply of public goods or those transfers which compensate for market imperfections. Our work aims firstly to review the concepts of rents and rent-seeking, and to develop a methodology for quantifying political rents in agricultural policy. We perform comparative analyses with the aim of calculating the ‘pure political rent’, based on the input-output approach for representative farms according to the EU FADN typology and on a decomposition of the Hicks–Moorsteen TFP index for the period 2004-2012 and 27 European Union Member States. The calculations of political rents show that historical payments are neither a rational nor a just solution. No attempts have yet been made in the literature to quantify political rents, even though this might lead to an improvement in the effectiveness of public expenditure. The original methodology is proposed for valuing these items.

Rent-seeking in agricultural policy revisited: a new look at the Common Agricultural Policy consensus

It is generally believed that agricultural interventionism represents the payment of political rents to farmers. We attempt to show that the concept of political rent known as the rent-seeking theory is not valid for agricultural policy. It is not justified to identify the entire subsidies paid to agriculture as a ‘political rent’, since political rents cannot be taken to include payments for the supply of public goods or those transfers which compensate for market imperfections. Our work aims firstly to review the concepts of rents and rent-seeking, and to develop a methodology for quantifying political rents in agricultural policy. We perform comparative analyses with the aim of calculating the ‘pure political rent’, based on the input-output approach for representative farms according to the EU FADN typology and on a decomposition of the Hicks–Moorsteen TFP index for the period 2004-2012 and 27 European Union Member States. The calculations of political rents show that historical payments are neither a rational nor a just solution. No attempts have yet been made in the literature to quantify political rents, even though this might lead to an improvement in the effectiveness of public expenditure. The original methodology is proposed for valuing these items.

Surplus measures and luenberger Hicks–Moorsteen productivity indicator

This paper extends to production theory some notions of compensated and equivalent variation analyzed in Luenberger (Econ Theory 7:445–462, 1996) in a consumer context. Along this line the Luenberger–Hicks–Moorsteen productivity indicator introduced in Briec and Kerstens (Econ Theory 23:925–939, 2004) is derived from these concepts for multi-output production technologies. The dual properties of this productivity indicator are analyzed and an aggregate indicator is introduced inspired from the resource function proposed in Luenberger (1996). A connection to a suitable Slutsky matrix is established.

Total factor productivity growth and regional competitive analysis of China’s star-rated hotels

This study investigates the total factor productivity (TFP) growth, technological progress, pure technical efficiency change, scale efficiency change, and mix efficiency change of star-rated hotels in China by employing a Hicks–Moorsteen index approach. The results show that the TFP of star-rated hotels in China had an annual average growth rate of 13.11%, mainly attributed to an annual average growth rate of operational efficiency of 21.85% and a mix efficiency growth rate of 13.52%. The growth rate of optimal production technology in the Western region markedly outperformed those in other regions and yet its growth rate of operational efficiency significantly underperformed. We also found that catch-up effects in the Central and Western regions were progressing in terms of operational efficiency and optimal production technology, respectively. The findings suggest that policy makers and practitioners should focus on TFP growth and its components, drawing the attention of star-rated hotels to upgrade their optimal production technology and enhance their operational efficiency as a means of improving TFP and competitiveness. Lastly, this study advances a new research perspective in efficiency assessment in the hotel industry by considering both financial and service production outputs.