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on Efficiency and Productivity |
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Issue of 2017‒01‒15
24 papers chosen by |
| By: | Alexander Murray |
| Abstract: | A partial productivity measure relates output to a single input. Total factor productivity (or TFP) relates an index of output to a composite index of all inputs. This report discusses the strengths and weaknesses of each type of productivity measure from theoretical and methodological perspectives. Different productivity measures may be useful for different analytical purposes, and no single measure provides a complete picture of an industry's productivity performance. The report then presents estimates of TFP and a suite of partial productivity measures for a set of natural resource-related industries in Canada. The three forestry products industries and the crop and animal production industry exhibited the best productivity performance over the 1990-2012 period across a variety of productivity measures, while oil and gas extraction and mining experienced the worst productivity performance. |
| Keywords: | Productivity, Total Factor Productivity, Multifactor Productivity, Labour Productivity, Natural Resources, Measurement, Canada, Agriculture |
| JEL: | D24 J24 O47 Q3 O51 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:sls:resrep:1620&r=eff |
| By: | Löschel, Andreas; Lutz, Benjamin Johannes; Managi, Shunsuke |
| Abstract: | We investigate the effect of the European Union Emissions Trading System (EU ETS) on the economic performance of manufacturing firms in Germany. Our difference-in-differences framework relies on several parametric conditioning strategies and nearest neighbor matching. As a measure of economic performance, we use the firm specific distance to the stochastic production frontier recovered from official German production census data. None of our identification strategies provide evidence for a statistically significant negative effect of emissions trading on economic performance. On the contrary, the results of the nearest neighbor matching suggest that the EU ETS rather had a positive impact on the economic performance of the regulated firms, especially during the first compliance period. A subsample analysis confirms that EU ETS increased the efficiency of treated firms in at least some two-digit industries. |
| Keywords: | Control of Externalities,Emissions Trading,Economic Performance,Manufacturing,Difference-in-Differences,Nearest Neighbor Matching,Stochastic Production Frontier |
| JEL: | Q52 D22 Q38 Q48 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cawmdp:91&r=eff |
| By: | Manthos Delis; Chrysovalantis Gaganis (Department of Economics, University of Crete, Greece); Iftekhar Hasan; Fotios Pasiouras |
| Abstract: | How does genetic diversity in the country of origin of a firm’s board members affect the corporate performance of these firms? The answer has important implications for the optimal synthesis of corporate boards of directors as a means to enhance firms’ profitability and value. Human genetic diversity captures deep-rooted social, cultural, psychological, physiological, and institutional characteristics that were shaped many years ago. Within-board differences in these characteristics—which modern relevant indices may fail to capture—can have a unique bearing on firm performance. In this study, we explore this question by bringing together data on the biological genetic variation of board members’ country of origin along with simple measures of corporate performance. We hypothesize that the diversity in the boardroom, in terms of genetic diversity within each director’s country of origin, can affect a firm’s performance. Although this article refers to genetic diversity in the total population of each board member’s country of origin, for simplicity we use the term “genetic diversity of the board.” To construct our diversity measure, we use information from BoardEx on the nationality of board members for a number of firms and attach country-specific genetic diversity values from Ashraf and Galor (2013) to each board member. Then, we calculate our measure of genetic diversity of boards as the standard deviation by firm-year of genetic diversity across the values given to each board member. We call this computation the “deviation effect” of genetic diversity. With this measure, we aim to examine whether including directors from countries with different levels of genetic diversity affects firms’ profitability and value. We are of course unaware about which genes these directors carry, and we do not claim to examine the direct effect of genomes on corporate performance. We also abstain from suggesting that a higher or a lower level of diversity in the country of origin is either beneficial or unfavorable for corporate performance. Thus, we do not relate corporate performance to the mean score of genetic diversity in the boardroom. What we do examine with the standard deviation is whether and to what extent deep-rooted differences in the directors’ countries of origin affect firm performance, irrespective of whether these differences come from a genetically more robust (less diverse) country or less robust (more diverse) country. We contend that it is the diversity in these deep-rooted elements that also shapes firm performance in unique ways. As an example, consider a U.K.-based firm with 10 directors, 8 of whom are British, 1 is Brazilian, and 1 Italian. The British directors are all assigned an equal score of B, the standard deviation of which is zero. Based on Ashraf and Galor (2013), the Brazilian director carries a score lower than B and the Italian a score higher than B. The presence of both the Brazilian and the Italian director increases the deviation of the board’s diversity. We seek to examine whether and to what extent this increase affects corporate performance. We are not considering whether the fact that the Brazilian (Italian) director has a score lower (higher) than B affects corporate performance. We test the impact of the deviation effect on firm performance, as measured by risk-adjusted returns and Tobin’s q, using a panel of up to 1,085 firms based predominantly but not exclusively in the United States and the United Kingdom from 1999 through 2012. We overcome the potential endogeneity problem by using two instrumental variables. These variables are constructed using the mean of migratory distance from East Africa and the mean of ultraviolet exposure in the board members’ country of origin, by firm and year. Our exploration of these variables is motivated by the implications of Ashraf and Galor (2013) as well as important findings in biology. The results show that genetic diversity plays an important role in affecting corporate performance. These findings hold even if we control for other elements of diversity, such as gender, culture, and nationality, which have been shown to have an important bearing on the efficiency and performance of corporate boards and firms. In keeping with the results of Ashraf and Galor (2013) regarding the effect of genetic diversity on economic development, we suggest that deep-rooted elements of diversity exist that were determined thousands of years ago and now play an important role in the functioning and performance of corporate groups. More specifically, we find that the deviation effect of genetic diversity is positive and statistically and economically significant. For a firm with an average risk-adjusted return, a one standard deviation increase in the deviation of diversity implies a 20.8% increase in risk-adjusted return. Also, an increase in the deviation of diversity by the same amount will increase Tobin’s q by approximately 6.9% for a firm with an average Tobin’s q in our sample. This positive effect on corporate performance is in line with an important strand of sociology and management literature, which posits that the performance of groups is enhanced only when the level of heterogeneity is considerable and irrespective of whether the country of origin has a higher or a lower score compared to the country in which the firm is headquartered. We view this as an important finding with specific implications for organizational science, management science, and financial economics. |
| Keywords: | Genetic diversity; corporate performance; nationality of board members |
| JEL: | M14 M50 |
| Date: | 2016–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:1604&r=eff |
| By: | Diewert, W. Erwin; Fox, Kevin J. |
| Abstract: | One of the problems with index number methods for computing TFP growth is that during recessions, these methods show declines in TFP and this seems to imply that technical progress is negative during these periods. This is rather implausible since it implies technological regress; i.e., that that the production frontier has contracted. The paper works out a nonparametric method where one can decompose TFP growth into two components: a technical progress component (i.e., a shift in the production frontier over time) and an inefficiency component that is due to the fixity of capital and labour in the short run. The new decomposition is illustrated using the new Bureau of Economic Analysis (BEA) Integrated Macroeconomic Accounts which facilitated the construction of a set of productivity accounts for two key sectors of the US private business sector: the Corporate Nonfinancial Sector and the Noncorporate Nonfinancial Sector. The analysis sheds light on productivity growth slowdowns over the period 1960 to 2014. |
| Keywords: | Total Factor Productivity, user costs, measures of technical progress, measures of technical and allocative inefficiency, nonparametric cost functions |
| JEL: | C43 C61 C67 C82 D24 E22 |
| Date: | 2016–06–30 |
| URL: | http://d.repec.org/n?u=RePEc:ubc:pmicro:erwin_diewert-2016-8&r=eff |
| By: | Konstantinos Chatzimichael; Pantelis Kalaitzidakis (Department of Economics, University of Crete, Greece); Vangelis Tzouvelekas (Department of Economics, University of Crete, Greece) |
| Abstract: | Rankings of academic departments are widely used by universities throughout the world as benchmarks to allocate efficiently their research funds to different departments, and further, as signals of high-quality education to attract or retain the most skillful and promising students and faculty. They are also used by academic departments themselves to define performance targets and shape optimal marketing strategies and further by academics and students when making their decisions on career advancements and investments in education, respectively. At aggregate level, rankings serve as informative policy instruments for national governments, as well as for country unions, in defining research budgets levels and optimally allocate them to domestic universities and country members, respectively. For instance, the development of Lisbon Agenda (2000) and the associated commitment of European Council (2005) to increase R&D funding in EU, were mainly triggered by the observed gap in leading-edge research between EU member countries and the U.S., as robustly evidenced by worldwide institutional rankings. In economic profession, there is a long tradition in ranking departments. Existing work commonly uses various measures of research output to rank departments. Laband (1985) used counts of citations to assess economics departments performance, while Yotopoulos (1961), and Niemi (1975) focused on number of articles published in top journals. Along the same lines, Yeager (1978) and Bairam (1978) considered total number of pages published in high-ranked journals. Recognizing that the quality of publications matters, Graveset al., (1982), and Scott and Mittias (1996) used AER-equivalent pages to adjust for journal-quality differences. Along the same line of argument, Conroy et al. (1994), and Dusansky and Veron (1998) looked also at AER-equivalent page counts using Laband and Piettes's (1994) updating of Liebowitz and Palmer's (1984) journal rank to weight journals. Similarly, Kalaitzidakis et al. (2003) provided a worldwide ranking of economics departments correcting further for biases arising from lagged journal weights and self-citations inclusions. There have been also rankings based on Ph.D. placements (Amir and Knauff, 2008) and averages of ranks statistics (Coupe, 2003). Most of the studies highlighted above focus solely on research output measures to rank economics departments such as number of articles, article pages, citations or combinations of them. Needless to say, such measures lack important information on research inputs use and thus might be considered as inappropriate, especially when comparisons are to be made. For instance, published articles and subsequently citations are likely to be proportionally related to faculty size. Similarly, differences in research funds, research environment and other research inputs between departments are likely to explain observed differences in research output produced. Hence, adjusting at least for some sort of inputs variations between departments is a necessary prerequisite prior comparing actual departments performance in order to obtain meaningful rankings. The important dimension of research inputs has been considered only by a limited number of studies in the field. At micro level (department level), Conroy et al. (1995) and Scott and Mittias (1996) ranked economics departments in U.S. based on productivity performance as measured by output per faculty. Using NRC (1995) survey data, Thursby (2000) tested for differences in quality ratings between economics departments in U.S. accounting for faculty size, number of federal grants, and expenditures on library acquisitions. At macro level (country level), Kirman and Dahl (1994) and Kocher and Sutter (2001) provided aggregated country rankings adjusting for research inputs such as financial resources and population. Finallly, Kocher et al. (2006) adopted a DEA approach to compile a productivity-based ranking of OECD countries using country's R&D expenditures, number of economics departments, and population as research inputs. Three important observations can be drawn from the existing literature as reviewed earlier. First, most of the work in the field neglects to adjust for differences in research inputs among departments, producing therefore less informative rankings, inappropriate for comparison purposes. On the other hand, the few exceptional studies that do consider for research inputs variations focus exclusively on U.S. Second, the majority of studies are based on journals rankings constructed over a certain period of time that, more often than not, does not coincide with the corresponding period of departments rankings. This implies that journal weights used to adjust for quality differences in publications are likely to misestimate the true quality of the journals at the time of investigation and subsequently the true performance of departments. Third, most of the existing work provides either university- or country-level rankings but does not combine them. It would be quite informative though to assess performance at both micro- and macro-level combining at the same time information from department and country rankings produced using the same methodology. In this paper, we assess the relative performance of economics departments in Europe using publication data in a core set of thirty-five top research journals in economics during the period 2007-11. Rather than focusing exclusively on output research measures, we assess performance on the basis of a publishing productivity index which allows to account for differences in research inputs among departments. The measurement of publishing productivity is based on counts of AER-equivalent articles per faculty using Kalaitzidakis' et al. (2011) updated journal weights computed over the same period with our study, overcoming thus any concerns associated with lagged-weights bias. Data on faculty size were obtained from an online search on departments websites at the time of investigation. Based on publishing productivity performance, comprehensive rankings are constructed at department level, as well as, at country level by aggregating research output and inputs of economics departments in each country. The distance of Greek economics departments from the top european departments is finally assessed. |
| Keywords: | economics departments, universities rankings, publishing productivity, Europe |
| JEL: | A11 A14 D24 I23 |
| Date: | 2016–09–20 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:1601&r=eff |
| By: | Matthew Calver and Alexander Murray |
| Abstract: | Between 1997 and 2014, multifactor productivity (MFP) in Canada's business sector industries grew at an annual rate of 0.02 per cent per year − essentially zero. In this report, we decompose aggregate MFP growth into contributions by industry and province. Two sets of results are presented: one based on the generalized exactly additive decomposition (GEAD) and one based on the CSLS decomposition. The two decomposition methods lead to very different conclusions. The GEAD suggests that the reallocation of inputs to the mining and oil and gas extraction industry in the oil-rich provinces were the primary drivers of MFP growth in Canada while the manufacturing sector, concentrated in Ontario and Quebec, dragged MFP growth down. The CSLS decomposition suggests precisely the opposite: mining and oil and gas was the main hindrance to Canada’s MFP performance while manufacturing was the major driver of MFP growth. The disagreement between the two methods is primarily attributable to the fact that the large increase in commodity prices (especially oil prices) over the 1997-2014 period increases the mining and oil and gas industry's contribution to MFP growth according to the GEAD while the CSLS decomposition does not treat such relative price effects as contributors to productivity growth. |
| Keywords: | Productivity, Total Factor Productivity, Multifactor Productivity, Canada |
| JEL: | D24 O51 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:sls:resrep:1619&r=eff |
| By: | Peter Howard-Jones (Bournemouth University, Executive Business Centre); Jens Hoelscher (Bournemouth University, Executive Business Centre); Dragana Radicic (University of Cambridge) |
| Abstract: | This study examines the productivity performance of Balkan firms within and outside the European Union (EU). In addition to evaluating the efficacy of membership it also studies the influence of loans, since evidence suggests a correlation between the macro- economic element of EU membership and the micro influence of loans. A multi treatment model is used to compare the effect on productivity of membership and loans, both separately and collectively, which in the case of loans allows a separate analysis of their influence on firms in non-member states. The use of conditional quantile regressions, which divide a frequency distribution into equal groups each containing the same fraction of the total population, measures the effect on productivity of membership and loans separately as treatment variables. This provides an analysis of where the treatment influence is greatest and identifies the significance of selected control variables on the outcome. The analyses are conducted for firms in all states and disaggregated to provide results for the manufacturing and service sectors. Within the full sample, the findings indicate that EU membership and loans have a positive effect on productivity; membership being more important than loans. Outside the EU, firms in receipt of loans are more productive than those without. However, the significance of both membership and loans is restricted to the lower end of the productivity distribution curve. The manufacturing sample shows that membership is positive across 70% of the distribution, while loans are restricted to the bottom quantiles, with rental capital also positively significant. In the services sector however, membership is significant up to 90% of the distribution, with loans at 60%. Foreign ownership, age and size are also significant across the productivity distribution curve. Policy implications indicate the advantages of EU membership allied to improvements in financial intermediation, particularly within the manufacturing sector. |
| Keywords: | Transition economies; Firm productivity; EU membership; Access to loans; Multi-level model; Quantile regression |
| JEL: | C D E F G O |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:bam:wpaper:bafes06&r=eff |
| By: | Nidhi Varshney, Chanchal Chawla |
| Abstract: | The banking system of India is featured by a large network of bank branches, serving many kinds of financial services of the people. There are currently 27 public sector banks in India out of which 19 are nationalised banks and 6 are SBI and its associate banks, and rest two are IDBI Bank and BharatiyaMahila Bank, which are categorized as other public sector banks. There are total 93 commercial banks in India. The purpose of this study is to compare the financial performance of two leading public sector banks of India i.e. State Bank of India and Punjab National Bank. Quantitative analysis was undertaken by looking at various sets of financial ratios that are routinely used to measure bank performance. The State Bank of India, popularly known as SBI is one of the leading bank of public sector in India. SBI has 14 Local Head Offices, 57 Zonal Offices and more than 13500 branch offices located at important cities throughout the country. On the other hand Punjab National Bank Founded in 1894, the bank has over 6,968 branches and over 9,656 ATMs across the country. The period of study taken is from the year 2007-08 to 2011-12. The main ratios that were employed put a particular focus on the banks liquidity, profitability, management capacity, capital structure and share performance as reliable indicators of a bank performance. Conclusions were then drawn from the computation of the relevant ratios that allowed the author to make an effective comparison of said banks. Key words: Credit Deposit Ratio, PNB, Net Profit Margin, Net worth Ratio, Financial Analysis, SBI Policy |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:vor:issues:2016-12-06&r=eff |
| By: | José-María Da-Rocha; Marina Mendes Tavares; Diego Restuccia |
| Abstract: | We assess the quantitative impact of firing costs on aggregate total factor productivity (TFP) in a dynamic general-equilibrium framework where the distribution of establishment-level productivity is not invariant to the policy. Firing costs not only generate static factor misallocation, but also a worsening of the productivity distribution contributing to large aggregate TFP losses. Firing costs equivalent to 5 year's wages imply a drop in TFP of more than 20 percent. Factor misallocation accounts for 20 percent of the productivity loss, a relatively small drop in TFP, whereas the remaining 80 percent arises from the endogenous change in the productivity distribution. |
| JEL: | E1 E6 O1 O4 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:23008&r=eff |
| By: | Friese, Maria; Heimeshoff, Ulrich; Klein, Gordon J. |
| Abstract: | This paper provides evidence that ownership and organization matters for the efficiency of provision of public services. In particular, we find that pure private ownership is more efficient than pure public ownership, followed by mixed ownership. The delegation of management in different legal forms also has an impact, highlighting the importance of the design of the government-operator relation. We apply a structural approach of production function estimation ensuring precise determination of total factor productivity for a panel of German refuse collection firms in the time period between 2000-2012. We project total factor productivity estimates (TFP) on ownership and organization. Our results are in line with the trade-offs implied by the property rights literature and provide important policy implications regarding the organization of public service provision. |
| Keywords: | incentive regulation,productive efficiency,refuse collection,public utility |
| JEL: | L00 L33 L50 L97 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:wwuifg:173&r=eff |
| By: | Clemens Struck (University College Dublin); Adnan Velic (Dublin Institute of Technology) |
| Abstract: | Following standard macroeconomic theory, a non-increasing long-run share of labor in income combined with a capital-labor substitution elasticity of less than unity implies that productivity growth should be labor-augmenting. Employing an industry decomposition for the U.S., we find that technical progress is factor neutral. However, we stress potential inflation measurement errors manifested in the form of non-positive long-term productivity growth in a number of industries. We illustrate that estimates of the bias of technical change are quite sensitive to these measurement issues. If aggregate inflation is annually overstated by as little as a third of a percentage point, technical progress is already over 50 percent higher in the labor-intensive sector than in the capital-intensive sector. Thus, even the presence of small positive inflation biases could very well mean that technical change is notably labor augmenting. |
| Keywords: | technical change, labor-augmenting, measurement error, inflation bias |
| JEL: | E1 E13 E31 O31 |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:tcd:tcduee:tep0117&r=eff |
| By: | Gugler, Klaus; Liebensteiner, Mario |
| Abstract: | We estimate cost functions to derive productivity growth using a unique database on costs and outputs of essentially all regulated Austrian gas distribution companies over the period 2002-2013, covering the times before and after the introduction of incentive regulation in 2008. We estimate a concave relation between total costs and time, and a significant one-off but permanent reduction in real costs after an imposed reduction in granted costs in the course of the introduction of incentive regulation. Our results imply that technological opportunities were higher in the early years of the sample than in later years, and that productivity growth grinded to a halt from 2008 on. We conclude that technological opportunities are exhausted (for the time being) in the Austrian gas distribution sector giving rise to an optimal general X factor (X-gen) of zero for the foreseeable future. (authors' abstract) |
| Keywords: | X-gen; Productivity; Regulation; Gas distribution |
| Date: | 2016–10 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus005:5221&r=eff |
| By: | Chrysovalantis Gaganis (Department of Economics, University of Crete, Greece) |
| Abstract: | Microfinance institutions which specialize on the provision of financial services to low-income clients and micro-entrepreneurs have grown significantly in recent years. Lützenkirchen and Weistroffer (2012) highlight that MFIs had extended loans to more than 200 million clients by the end of 2010, whereas through various socio-economic ties of the borrowers and their families, microfinance has influenced the lives of around 1 billion people in emerging and developing countries. Another particular characteristic of the MFIs’ borrowers is that they usually lack credit history and collateral which limits their access to financing from traditional commercial banks (Banerjee and Duflo, 2007). Therefore, it is not surprising that MFIs have attracted considerable attention by academics and policy makers, with recent studies focusing on a variety of topics like the impact of microfinance on poverty or child health outcomes (Imai et al., 2012; DeLoach and Lamanna, 2011), competition between microfinance non-governmental organizations (Ly and Mason, 2012), microfinance and female empowerment (Ngo and Wahhaj, 2012), the use of credit scoring models from MFIs (Blanco et al., 2013; Cubiles-De-La-Vega et al., 2013), the diversification benefits from adding microfinance funds to a portfolio of risky international assets (Galema et al., 2011), the drivers of buffer capital (Tchuigoua, 2016), and the determinants of governance quality (Tchuigoua, 2015). The aim of the present study is twofold. The first aim is to provide an overall measure of the performance of MFIs. As discussed in Devinney et al. (2010), the performance of firms is of central interest to managers, researchers and policy makers; however, there is little convergence of opinion on how performance should be measured. To this end, Devinney et al. (2010) argue in favour of an overall measure of performance. This becomes even more crucial in the case of MFIs, due to the double challenge that they face. More detailed, MFIs not only have to provide financial services to the poor (outreach), but they also have to cover their costs to avoid bankruptcy (sustainability). Furthermore, as mentioned in von Stauffenberg et al. (2003) all performance indicators tend to be of limited value when examined in isolation and this is particularly the case for the profitability indicators of MFIs. They also highlight that to understand how an institution achieves its profits the analysis must also take into account other indicators that influence the operational performance of the institution, such as operational efficiency and portfolio quality. Finally, the profitability analysis is further complicated by the fact that a significant number of MFIs receive grants and subsidized loans. Therefore, ideally various dimensions should be taken simultaneously into account in the assessment of their performance. Nonetheless, as discussed in Weber and Luzzi (2007) very few attempts have been made to aggregate the numerous indicators of MFI’s performance into a single measure and most of the studies simply compare the financial condition of MFIs on the basis of univariate tests of individual ratios such as the return on assets (e.g. Bi and Pandey, 2011; Agarwal and Sinha, 2010). Zeller et al. (2003) propose the construction of an overall measure; however, their suggestions are limited to the assignment of arbitrary weights to the indicators or the derivation of weights through principal components analysis (e.g. Weber and Luzzi, 2007). A few recent papers also estimate the efficiency and/or productivity of MFIs using frontier techniques (e.g. Servin et al., 2012; Wijesiri et al., 2015; Wijesiri and Meoli, 2015), which provide an overall score. However, the majority of these studies tend to measure how efficient the MFIs are in transforming inputs (e.g. number of credit officers, total assets) to outputs (e.g. financial revenue), while ignoring other aspects like portfolio risk and capital strength.[1] In this paper, I follow a different approach, and I propose the use of the PROMETHEE II multicriteria method that summarizes both the financial and social performance of MFIs in a single score of relative performance on the basis of pairwise comparisons across a set of often conflicting criteria.[2] The second aim of the present study is to explain differences in the overall performance indicator, obtained from the PROMETHEE II method, on the basis of firm-specific and country-specific attributes. The investigation of the determinants of performance has attracted the interest of researchers from the fields of international business, strategic management, and finance (e.g. McGahan and Porter, 2002; Joh, 2003; Short et al., 2007; McGahan and Victer, 2010). However, MFIs are considerably under-research compared to non-financial firms and traditional banking institutions. The few existing studies examine the impact of firm-level attributes such as corporate governance and legal status (Hartarska, 2005; Mersland and Strøm, 2009; Tchakoute-Tchuigoua, 2010) or country-level characteristics such as regulations, macroeconomics, and institutional development (Cull et al., 2011; Ahlin et al., 2011) on single indicators of the profitability and growth of MFIs. |
| Keywords: | microfinance, performance, Promethee II |
| JEL: | G21 G10 |
| Date: | 2016–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:1603&r=eff |
| By: | Jasmin Thomas |
| Abstract: | Productivity growth results in part from investment in information and communications technologies (ICT). To better understand Canada’s poor productivity growth relative to the United States since 2000, this report provides a detailed examination of ICT investment trends in the two countries. The report finds that real ICT investment in the total economy in Canada has yet to recover from the 2008-2009 recession, while it has not suffered the same fate south of the border. Between 2008 and 2014 real ICT investment in Canada fell 1.0 per cent per year, compared to a 2.9 per cent per year increase in the United States. The gap was even greater for real ICT investment per job, down 1.8 per cent per year in Canada versus a 2.8 per cent annual increase in the United States. The weaker ICT investment growth in Canada resulted in a large increase in the Canada-US ICT investment gap from 31.6 percentage points to 43.7 points, as nominal ICT investment per job fell from 68.4 per cent of the US level in 2008, the highest value ever achieved, to 56.3 per cent in 2014. |
| Keywords: | Investment, Information and Communication Technology, Information Technology, ICT, IT, Productivity, Industries, Professional Services, Cultural Industries, Canada, U.S. |
| JEL: | E22 O16 D24 L60 L70 L80 L90 N72 N32 N12 O51 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:sls:resrep:1617&r=eff |
| By: | Bachtrögler, Julia |
| Abstract: | This study investigates the heterogeneity of European NUTS-2 regions with regard to their ability to take advantage of European Union (EU) structural funds aimed at convergence. It considers a concept of absorptive capacity based on regional policy design, and additionally accounts for the programming period 2007-2013 in the empirical analysis. A fuzzy regression discontinuity design allowing for heterogeneous treatment effects is applied to evaluate convergence funds in 250 NUTS-2 regions from 2000 (and 1989) to 2013. The main results suggest a positive conditional impact of funds payments on regional GDP per capita growth. However, based on a time-varying treatment effects model, we are able to identify a deterioration in the effectiveness of convergence funds during the programming period 2007-2013. Furthermore, the analysis reveals an inverted U-shaped relationship between the share of committed funds paid out and GDP per capita growth. The latter finding indicates that the marginal benefits from EU convergence funds might be decreasing. (author's abstract) |
| Keywords: | Structural Funds; Heterogeneous Treatment Effects; Regional Heterogeneity; Absorptive Capacity; Cohesion; European Union |
| Date: | 2016–08 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus005:5157&r=eff |
| By: | Daniele Moschella; Federico Tamagni; Xiaodan Yu |
| Abstract: | This article investigates the characteristics of high-growth (HG) firms in Chinese manufacturing, and further explores the effects of firm characteristics on persistence of high-growth. We employ a multidimensional definition of HG firms that simultaneously accounts for growth of sales and employment. Exploiting a representative panel covering the period of the Chinaùs miracle, we find that HG firms outperform other firms, showing higher productivity, higher profitability, larger investment intensity, higher sales from product innovation, lower interest expenses and lower leverage. HG firms are also relatively young, larger in size, more often exporters and more concentrated in non-State-controlled companies. However, regression analysis suggests that none of the indicators of structural characteristics and performance considered above displays any statistical association with the ability to persistently replicate high-growth over time. The results speak against the long-run effectiveness of policies supporting the creation and backing of high-growth firms. |
| Keywords: | Entrepreneurship, Firm growth, High-growth firms, Persistent high-growth firms |
| Date: | 2017–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2017/03&r=eff |
| By: | Emran, M. Shahe; Shilpi, Forhad |
| Abstract: | This paper uses a framework that goes beyond rural-urban dualism and highlights the role of small town economy (STE) in understanding structural change in a rural economy such as Bangladesh. It provides a theoretical and empirical analysis of the role of agricultural productivity in structural transformation in the labor market, with a focus on the differences between a village economy and a small town economy. The empirical work is based on a general equilibrium model that formalizes the demand and labor market linkages: the STE draws labor away from the rural areas to produce goods and services whose demand may depend largely on rural income. The theory clarifies the role played by the income elasticity of demand and the elasticity of wage with respect to productivity increase in agriculture. For productivity growth to lead to a demand effect, the elasticity of wage has to be lower than a threshold. When the demand for goods and services produced in small towns comes mainly from the adjacent rural areas, the demand effect can more than offset the negative wage effect, and lead to higher labor allocation to the production of town good. Using rainfall as an instrument for agricultural productivity, the empirical analysis finds a significant positive effect of agricultural productivity shock on rice yield and agricultural wages. The evidence shows that productivity shock increases wages more in the rural sample when compared to the STE sample. But structural change in employment is more pronounced in the STE sample. In the rural sample, it increases employment only in small scale manufacturing and services. In contrast, a positive productivity shock has large and positive impacts on employment in construction and transport, education, health and other services, and manufacturing employment in larger scale enterprises located in small towns and cities. Agricultural productivity growth is found to induce structural transformation within the services sector in small towns, with employment in skilled services growing at a faster pace than that of low-skilled services. |
| Keywords: | Agricultural Productivity, Small Town Economy, Dualism, Employment in Large Firms, Employment Growth, Structural Transformation |
| JEL: | D5 O1 O12 |
| Date: | 2017–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:75938&r=eff |
| By: | Breunig, Christoph; Kummer, Michael; Ohnemus, Jorg; Viete, Steffen |
| Abstract: | Missing values are a major problem in all econometric applications based on survey data. A standard approach assumes data are missing-at-random and uses imputation methods, or even listwise deletion. This approach is justified if item non-response does not depend on the potentially missing variables' realization. However, assuming missing-at-random may introduce bias if non-response is, in fact, selective. Relevant applications range from financial or strategic firm-level data to individual-level data on income or privacy-sensitive behaviors. In this paper, we propose a novel approach to deal with selective item nonresponse in the model's dependent variable. Our approach is based on instrumental variables that affect selection only through potential outcomes. In addition, we allow for endogenous regressors. We establish identification of the structural parameter and propose a simple two-step estimation procedure for it. Our estimator is consistent and robust against biases that would prevail when assuming missingness at random. We implement the estimation procedure using firm-level survey data and a binary instrumental variable to estimate the effect of outsourcing on productivity. |
| Keywords: | endogenous selection,IV-estimation,inverse probability weighting,missing data,productivity,outsourcing,semiparametric estimation |
| JEL: | C14 C36 D24 L24 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:16092&r=eff |
| By: | Diewert, W. Erwin; Fox, Kevin J. |
| Abstract: | Using the new Bureau of Economic Analysis (BEA) Integrated Macroeconomic Accounts as well as other BEA data, we construct a set of productivity accounts for two key sectors of the US economy: the Corporate Nonfinancial Sector (Sector 1) and the Noncorporate Nonfinancial Sector (Sector 2). Calculating user costs of capital based on, alternatively, ex post and predicted asset price inflation rates, we provide alternative estimates for capital services and Total Factor Productivity growth for the two sectors. Rates of return on assets employed are also reported for both sectors. Finally, the paper compares rates of return on assets employed and TFP growth rates when the land and inventory components are withdrawn from the asset base. |
| Keywords: | User cost of capital, Total Factor Productivity, rate of return on assets, Integrated Macroeconomic Accounts, Bureau of Economic Analysis, ex post and |
| JEL: | B25 C43 C82 D24 E22 E43 |
| Date: | 2016–06–30 |
| URL: | http://d.repec.org/n?u=RePEc:ubc:pmicro:erwin_diewert-2016-7&r=eff |
| By: | Fornaro, Paolo; Luomaranta, Henri |
| Abstract: | We analyze the productivity contribution of firms in the Finnish business sector, using data from 2002 until 2014, and assess the role of the dependency status (i.e. whether they are owned, at least partially, by a mother company) of small and medium enterprises in the manufacturing and services industries, together with the whole private business sector. We find that dependent firms have provided a larger contribution to aggregate productivity growth, compared to the independent ones, regardless of the industry, size class and age groups considered. This result is mainly driven by the better reallocation of labour among dependent companies and by the positive productivity contribution of dependent entrants. Inside the dependent category, the foreign controlled firms contribute more to the aggregate productivity than the other dependent companies due to even more efficient reallocation of labour inputs. Moreover, we find that dependent firms tend to reach their peak productivity earlier than their independent counterparts. Finally, we examine the subgroup of high growing enterprises and find that the positive effect of dependencies on the productivity contribution holds also for this class of firms. |
| Keywords: | Productivity, decomposition, dependencies, small and medium firms |
| JEL: | O12 O14 O47 |
| Date: | 2017–01–10 |
| URL: | http://d.repec.org/n?u=RePEc:rif:wpaper:47&r=eff |
| By: | Michael Doumpos; Chrysovalantis Gaganis (Department of Economics, University of Crete, Greece); Fotios Pasiouras |
| Abstract: | Corporate diversification has been characterized as a central topic of research in the literature with existing studies investigating various issues like its relationship with ownership, top management characteristics, information asymmetry, and organizational divisionalization, to name a few. Perhaps the most well researched strand of this literature is the one linking diversification and performance (Chatterjee and Wernerfelt, 1991; Palich et al., 2000), with early studies going back to the work of Rumelt (1982). However, this topic continues to be central in the research agenda of banking, finance, and management scholars (e.g. Chakrabarti et al, 2007; Goddard et al., 2008; Elsas et al., 2010). One potential reason is that despite the large number of studies, the literature has not yet reached maturity, as it is evident by the little agreement that exists at both the theoretical and empirical level (Palich et al., 2000). An important issue that has been highlighted in the case of non-financial firms is that while some studies examine the association between diversification and risk-return performance, the vast majority of the literature does not take risk into account (Bettis and Mahajan, 1985). This is surprising considering the importance of risk in managerial decision making (e.g. Miller and Bromiley, 1990) and the theoretical associations between diversification and risk (see e.g. Chang and Thomas, 1989). Additionally, the few studies that investigate the risk-return performance traditionally rely on the standard deviation of return on assets as a measure of risk, an approach that has also been used in studies in banking (e.g. Stiroh, 2004; Goddard et al., 2008). While this risk metric captures the instability of returns, it fails to take into account potential trade-offs, and it does not provide an overall indicator of exposure to the various risks. Yet, the idea that gains on one dimension must be potentially sacrificed on another dimension (i.e. trade-off) is central in the analysis of financial economics and bank management (Thakor, 2014). Some banking studies have partially improved upon this by relating diversification to risk using the Z-score index, an indicator of a bank’s probability of insolvency (e.g. Stiroh, 2004; Mercieca et al., 2007). This index takes into account not only the standard deviation of return on assets but also the average return on assets and the average equity to assets over a fixed time period. Still, the Z-score is not without its drawbacks. First, there is no guidance as for the number of years that have to be used for the calculation of the standard deviation, with many studies relying on just two or three years. Yet, as shown in Delis et al. (2014) the number of periods considered for the construction of the variance component significantly affects the results. In addition, the requirement of having data for numerous continuous years imposes some restrictions on the number of banks that can be eventually assessed with this kind of analysis. Third, and most importantly, the Z-score focuses on profitability and capitalization ignoring other aspects like liquidity, asset quality, and cost management. In general, there appears to be limited work in integrating various categories of risk exposures and incorporating risk into performance measures, an approach that could offer the possibility to assess the firm exposures along different dimensions (Miller, 1998; Chang and Thomas, 1989). At the same time, an increasing number of studies highlight the need to take into account the multidimensionality of performance, instead of focusing on individual measures like profits (see e.g. McKiernan and Morris, 1994; Devinney et al., 2010; Kyrgidou and Syropoulou, 2013). Motivated by the above discussion, we aim to re-examine the impact of diversification on risk and return, while proposing a methodological framework that integrates various bank characteristics into an overall indicator of financial strength. Thus, we attempt to bring together the literature on diversification and the one on the multidimensional character of firm performance, an issue that has not been properly explored, despite having been suggested as an avenue of future research for over two decades (see Nguyen et al., 1990). For various reasons discussed below, we opt for an application in the banking; however, our methodological approach may be applied in any industry using appropriate financial ratios or other indicators of risk and performance. |
| Keywords: | Diversification, overall financial strength, multidimensional performance, banking, multicriteria |
| JEL: | G10 G20 |
| Date: | 2016–09–22 |
| URL: | http://d.repec.org/n?u=RePEc:crt:wpaper:1602&r=eff |
| By: | Sokvibol, Kea |
| Abstract: | Dissertation for Master of Economics and Management of Agriculture Northwest A&F University. Advisor: Professor Li Hua |
| Keywords: | Crop Production/Industries, Production Economics, |
| Date: | 2016–11 |
| URL: | http://d.repec.org/n?u=RePEc:ags:thesms:251836&r=eff |
| By: | Amit Batabyal; Peter Nijkamp |
| Abstract: | We analyze inefficiency and inequality associated with the use of creative capital to produce a final good in a regional economy. Specifically, we first study a case in which the individual creative capital units are perfect substitutes in the production of the final good. We show that the equilibrium outcome is inefficient and that there is too little application of effort. Second, we define an indicator of inequality and show that an increase in inequality enhances efficiency and that it is, in principle, possible to achieve complete efficiency. Third, we focus on the case where the individual creative capital units are perfect complements and show that the equilibrium outcome is, once again, inefficient with too little effort application. Finally, we contend that our theoretical results provide a possible rationale for the observed income inequality in cities and regions in which the activities of the creative class constitute a large part of all economic activities. |
| Keywords: | Creative Capital; Inefficiency; Inequality |
| JEL: | R11 D20 |
| Date: | 2016–12 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwrsa:ersa16p75&r=eff |
| By: | Wanzenböck, Iris; Piribauer, Philipp |
| Abstract: | In this paper we estimate space-time impacts of the embeddedness in R&D networks on regional knowledge production by means of a dynamic spatial panel data model with non-linear effects for a set of 229 European NUTS-2 regions in the period 1999-2009. Embeddedness refers to the positioning in networks where nodes represent regions that are linked by joint R&D endeavours in European Framework Programmes. We observe positive immediate impacts on regional knowledge production arising from increased embeddedness in EU funded R&D networks, in particular for regions with lower own knowledge endowments. However, long-term impacts of R&D network embeddedness are comparatively small.(authors' abstract) |
| Keywords: | R&D networks; European Framework Programme; regional knowledge production; dynamic spatial panel data model; space-time impacts |
| Date: | 2015–09 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wus005:4652&r=eff |