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on Efficiency and Productivity |
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Issue of 2022‒07‒11
nine papers chosen by |
| By: | Lafond, François; Goldin, Ian; Koutroumpis, Pantelis; Winkler, Julian |
| Abstract: | We review recent research on the slowdown of labor productivity and examine the contribution of different explanations to this decline. Comparing the post-2005 period with the preceding decade for five advanced economies, we seek to explain a slowdown of 0.8 to 1.8pp. We trace most of this to lower contributions of TFP and capital deepening, with manufacturing accounting for the biggest sectoral share of the slowdown. No single explanation accounts for the slowdown, but we have identified a combination of factors which, taken together, accounts for much of what has been observed. In the countries we have studied, these are mismeasurement, a decline in the contribution of capital per worker, lower spillovers from the growth of intangible capital, the slowdown in trade, and a lower growth of allocative efficiency. Sectoral reallocation and a lower contribution of human capital may also have played a role in some countries. In addition to our quantitative assessment of explanations for the slowdown, we qualitatively assess other explanations, including whether productivity growth may be declining due to innovation slowing down. |
| JEL: | O40 E66 D24 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:amz:wpaper:2022-08&r= |
| By: | Fall, François Seck; Tchakoute Tchuigoua, Hubert; Vanhems, Anne; Simar, Léopold (Université catholique de Louvain, LIDAM/ISBA, Belgium) |
| Abstract: | The main objective of this study is to assess the impact of unobserved heterogeneity on microfinance social efficiency analysis . Based on recent nonparametric techniques and directional distances, we identify a latent heterogeneity factor related to the microfinance institute (MFI) manager’s ability to promote women, independent of MFI size . We test for the significance of this unobserved factor and analyze the impact of MFI social inefficiency measures . Using a cross-country sample of 501 MFIs in 2011 from six main regions of the world, our findings reveal a significant effect of unobserved heterogeneity on the frontier and hence stress the importance of subjective factors in defining the set of production possibilities. We assess the robustness of our findings with the considered profit-oriented status and analyze the link between our unobserved heterogeneity factor and institutional and socioeconomic indicators. |
| Keywords: | OR in Developing Countries ; Microfinance ; Gender ; Social Efficiency ; Unobserved Heterogeneity ; Nonparametric Robust Frontier Models |
| Date: | 2022–03–11 |
| URL: | http://d.repec.org/n?u=RePEc:aiz:louvad:2022010&r= |
| By: | António Afonso; José Alves |
| Abstract: | We assess the consequences of fiscal consolidation episodes on public sector efficiency (scores) for 35 OECD countries for the 2007-2020 period. We find that fiscal consolidations improve public sector efficiency and results are robust across efficiency models. Moreover, peripheral euro-area economies and economies with debt-to-GDP ratios between 60% and 90% are those whose public sector efficiency scores improve more when fiscal consolidation episodes occur. The evidence that fiscal consolidations enhance spending efficiency is an additional argument for fiscal consolidations, from a policy perspective. |
| Keywords: | fiscal consolidation episodes, government spending efficiency, panel data, OECD |
| JEL: | C23 D61 H21 E62 H63 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9761&r= |
| By: | Daraio, Cinzia; Simar, Léopold (Université catholique de Louvain, LIDAM/ISBA, Belgium) |
| Abstract: | Nonparametric methods have been widely used for assessing the performance of organizations in the private and public sector. The most popular ones are based on envelopment estimators, like the FDH or DEA estimators, that estimate the attain- able sets and its efficient boundary by enveloping the cloud of observed units in the appropriate input-output space. The statistical properties of these flexible estimators have been established. However these nonparametric techniques do not allow to make sensitivity analysis of the production outputs to some particular inputs, or to infer about marginal products and other coefficients of economic interest. On the contrary, parametric models for production frontiers allow richer and easier economic interpre- tation but at a cost of restrictive assumptions on the data generating process. In addition, the latter rely mostly on regression methods fitting the center of the cloud of observed points. In this paper we offer a way to avoid these drawbacks and provide approximations of these coefficients of economic interest by “smoothing” the popular nonparametric estimators of the frontiers. Our approach allows to handle fully multi- variate cases. We describe the statistical properties for both the full and the partial (robust) frontiers. We consider parametric but also flexible approximations based on local linear tools providing local estimates of all the desired partial derivatives and we show how to deal with environmental factors. An illustration on real data from European Higher Education Institutions (HEI) shows the usefulness of the proposed approach. |
| Keywords: | Nonparametric production frontiers ; DEA ; FDH ; partial frontiers ; directional distances ; linear approximations ; local linear approximations |
| JEL: | C1 C14 C13 |
| Date: | 2022–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:aiz:louvad:2022017&r= |
| By: | Harasztosi, Péter; Savšek, Simon |
| Abstract: | In this paper, we empirically assess repercussions of the pandemic on the firm-level productivity worldwide. COVID-19 shock was very heterogeneous across sectors. Our findings show that firms' responses to the shock also varied within sectors: more productive firms coped with the crisis better in terms of closures and employment adjustments. Besides, they were more likely to speed up some digitalization processes. These findings imply that the recent crisis could amplify the difference between highly productive and less productive firms. As regards the governments' policy measures, we find strong utilization at the firm level, but very little differentiation across productivity quantiles, suggesting room for a more targeted approach in the reminder of the pandemic. |
| Keywords: | Covid-19,Productivity,Enterprise Survey |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:eibwps:202209&r= |
| By: | Takashi Kamihigashi (Center for Computational Social Science (CCSS) and Research Institute for Economics and Business Administration (RIEB), Kobe University, JAPAN); Yosuke Sasaki (Center for Computational Social Science (CCSS) and Research Institute for Economics and Business Administration (RIEB), Kobe University, JAPAN) |
| Abstract: | Numerous empirical studies suggest that a technology change is associated with an increase in income inequality. The Gini coefficient (or the Gini index) is commonly calculated to quantify income inequality and analyze the relationship between inequality and other economic variables. However, the availability of Gini index data in a time series (e.g., five-year data) is sparse. Thus, it is difficult to study dynamic effects in panel data. This study utilizes the relative share of income as an inequality measure to analyze the interactions between cross-country income inequality and multi-factor productivity. Additional economic variables are also considered to inform the analysis further. Using the relative share of income enables observation of the long-term relationship dynamics between the two variables of interest because the necessary data are available for individual countries. Panel data are also available for cross-country factors. This study is the first to show that multi-factor productivity has a relationship with income inequality, based on understanding the static and dynamic effects. This study defines a model with some lags of the variable to capture the “dynamic effects.” The estimation method is the panel vector autoregression (Sigmund & Ferstl (2019)[35]) with generalized method of moments (Blundell & Bond (1998)[4]). This method determines the multi-period structure of multi-factor productivity and income inequality. Overall, this approach identifies the dynamic effects of multi-factor productivity on income distribution, which is a novel finding that requires further analysis. |
| Keywords: | Income inequality; Multi-factor productivity; Cross-country; Panel vector autoregression |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:kob:dpaper:dp2022-31&r= |
| By: | Deniz Igan; Ali Mirzaei; Tomoe Moore |
| Abstract: | We use firm-level data to provide some early evidence on the effectiveness of COVID-19 economic policy packages. Our empirical strategy relies on the varying degree of vulnerability to the pandemic across industries. We find a robust association of fiscal stimulus with changes in firm performance indicators (as measured by sales-to-assets ratio, profit margin, interest coverage ratio as well as probability of default) in pandemic-prone sectors. We also observe marginal effects of monetary policy on the sales-to-assets ratio and of foreign exchange intervention on the interest coverage ratio in the hardest-hit firms. These results broadly survive a battery of exercises to address endogeneity. Additionally, we show that firms with a better financial position are more likely to take advantage of the stimulus packages to withstand the pandemic shock. Overall, these provide preliminary evidence suggesting that policy interventions have bought time for the hardest-hit industries, by supporting turnover and improving liquidity. |
| Keywords: | economic stimulus, pandemic-prone, COVID-19, policy effectiveness |
| JEL: | G01 G14 G28 E65 |
| Date: | 2022–05 |
| URL: | http://d.repec.org/n?u=RePEc:bis:biswps:1014&r= |
| By: | Wang, Sophie Xuefei; Bansak, Cynthia |
| Abstract: | This study examines the impacts of caregiving by grandparents on children's academic performance in China, using data from the China Family Panel Studies (CFPS 2010 and 2014). Applying pooled OLS, instrumental variables and fixed-effects models with panel data estimation techniques, we find evidence that grandparents appear to have an adverse effect on the test scores of their school-age grandchildren. We further examine the mechanisms of this negative effect. Our results suggest that the education of grandparents plays an important role on the success of grandchildren and that increased schooling of grandparents can mitigate the negative effects of non-parental caregivers; thus, there are potential positive intergenerational impacts as grandparents become more educated themselves. When examining additional channels depressing test scores, we find evidence of grandparents' tendency to overindulge single-child grandchildren and grandsons. Lastly, it also appears that the common parenting practices of grandparents are detrimental to childhood development. |
| Keywords: | children,grandparents,instrument variable,academic performance,China |
| JEL: | I25 J13 O53 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:1100&r= |
| By: | Stefan Jestl (The Vienna Institute for International Economic Studies, wiiw) |
| Abstract: | This paper explores the effects of industrial robots and information and communication technology (ICT) on regional employment in EU countries. The empirical analysis relies on a harmonised comprehensive regional dataset, which combines business statistics and national and regional accounts data. This rich dataset enables us to provide detailed insights into the employment effects of automation and computerisation in EU regions for the period 2001-2016. The results suggest relatively weak effects on regional total employment dynamics. However, employment effects differ between manufacturing and non-manufacturing industries. Industrial robots show negative employment effects in local manufacturing industries, but positive employment effects in local non-manufacturing industries. While the negative effect is concentrated in particular local manufacturing industries, the positive effect operates in local service industries. IT investments show positive employment effects only in local manufacturing industries, while CT investments are shown to be irrelevant for employment dynamics. In contrast, software and database investments have had a predominantly negative impact on local employment in both local manufacturing and non-manufacturing industries. |
| Keywords: | Industrial robots, ICT, EU labour markets, employment effects |
| JEL: | J23 L60 O33 R11 |
| Date: | 2022–06 |
| URL: | http://d.repec.org/n?u=RePEc:wii:wpaper:215&r= |