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on Efficiency and Productivity |
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Issue of 2023‒10‒30
twelve papers chosen by |
| By: | Bart van Ark (The Productivity Institute, The University of Manchester); Dirk Pilat (The Productivity Institute, The University of Manchester); Klaas de Vries (The Conference Board) |
| Keywords: | productivity, G20, total factor productivity |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:anj:wpaper:038&r=eff |
| By: | Mohan, Preeya; Strobl, Eric |
| Abstract: | While Caribbean Small Island Developing States (SIDS) have been exposed to frequent external shocks in the past, the Coronavirus disease of 2019 (COVID-19) pandemic is like no other, representing the largest economic shock experienced globally in decades. The objective of this paper is to contribute to a better understanding of the innovation strategy and production efficiency of Caribbean firms during COVID-19. More specifically, it adopted a Stochastic Frontier Analysis (SFA) to investigate COVID-19, innovation, and technical efficiency for 13 Caribbean countries using the Innovation, Firm Performance, and Gender (IFPG) firm-level dataset. The results indicate that firms expect average technical efficiency to fall by over 100 percent because of COVID-19. Pre-COVID-19, 39 percent of firms implemented general innovations (product, process, organizational, and marketing) over the past three years, and 50 percent green innovations (environmental improvements), while the pandemic negatively affected 42 percent of these innovations. Firms that carried out general innovations experienced a positive effect on technical efficiency, while green innovations had a negative effect. During COVID-19 only 12 percent of firms initiated general innovations and 17 percent green innovations. These general innovations improved technical efficiency, while innovations that were affected by COVID-19 had a negative effect, and green innovations did not necessarily have a positive effect. |
| Keywords: | innovation;green innovation;COVID-19;production function;technical efficiency;stochastic frontier analysis;small islanddeveloping states |
| JEL: | D22 D24 O32 Q55 |
| Date: | 2023–03 |
| URL: | http://d.repec.org/n?u=RePEc:idb:brikps:12739&r=eff |
| By: | Jaumandreu, Jordi; Lopez, Rigoberto |
| Abstract: | We explore the evolution of productivity and markups in U.S. food and beverage manufacturing from 1959 through 2018, paying particular attention to the latest 20 years. Using the Census-based NBER-CES Manufacturing Productivity Dataset, we estimate a translog production function which allows for Hicks-neutral and labor-augmenting technical change and measure the unobserved productivity growth. The results show that, in contrast to general manufacturing, productivity growth in food manufacturing has been driven more by Hicks-neutral productivity than by labor-augmenting productivity, and that the growth of productivity has been rather slow. Moreover, markups in food manufacturing have been more modest than found in previous studies of market power in the food industries and comparable to those of general manufacturing. In contrast to previous studies, we find no evidence of markups rising in either food manufacturing or general manufacturing in the last 20 years. We attribute three reasons by which these results contrast with the generalized beliefs about raising markups, that are simultaneously possible explanations for the puzzles that we detect in our data. These are: accounting problems that may explain the rise that we see before the 2000s: possible changes in the value of input elasticities associated with biased technological change that should be carefully considered; and aggregation of firm-level markups that should be done avoiding spurious correlation. |
| Keywords: | Agribusiness, Productivity Analysis |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae23:338556&r=eff |
| By: | Fernando Alexandre (NIPE/Center for Research in Economics and Management, University of Minho, Portugal); Diogo Ferreira (NIPE/Center for Research in Economics and Management, University of Minho, Portugal); Sandro Mendonça (Business Research Unit (BRU-IUL), University Institute of Lisbon; Research Unit on Complexity and Economics (UECE), Research in Economics and Mathematics (REM), Lisbon School of Economics & Management (ISEG), University of Lisbon; Science Policy Research Unit (SPRU), University of Sussex.); Miguel Portela (NIPE/Center for Research in Economics and Management, University of Minho, Portugal; IZA, Bonn) |
| Abstract: | This paper evaluates the effectiveness of R&D subsidies, provided by the European Regional Development Funds, on firms’ productivity. Using detailed longitudinal firm-level data covering the period 2007-2019, we employ state of the art differences-in-differences estimators to evaluate the impacts of R&D grants. Positive causal effects on gross value added and labour productivity are discernible for micro- and small-sized firms participating in co-promotion but not in individual projects. However, these effects seem to be elusive. No evidence of a positive effect of these grants on firm performance for medium- and large-sized firms or for individual R&D projects is found. This investigation contributes to a more comprehensive understanding of the relative effectiveness of productivity enhancement programs. |
| Keywords: | R&D grants; productivity; European funds; co-promotion |
| JEL: | D22 H25 L25 L52 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:nip:nipewp:08/2023&r=eff |
| By: | Phu Nguyen-Van; Ngoc Minh Nguyen; Ngoc Anh Nguyen |
| Abstract: | We consider the capital productivity of a panel data set of 10, 200 Vietnam state-owned enterprises over the period 2010-2018, using a stochastic frontier production modelling. We discover there exists an overutilization of the physical capital and more importantly, diversion of the capital stock. This diversion may be due to a waste of capital stocks or to a special form of bribery we call "hidden overhead". The very high diversion rate, 69% on average, calls for a profound reform of the sector. |
| Keywords: | Productivity; stochastic production frontier; hidden overhead |
| JEL: | E20 O53 P20 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:drm:wpaper:2023-29&r=eff |
| By: | Martin Fleming (The Productivity Institute) |
| Keywords: | Enterprise, ICT, Productivity, Software |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:anj:wpaper:037&r=eff |
| By: | Christopher P. Chambers; Alexis Akira Toda |
| Abstract: | We prove that when individual firms employ constant-returns-to-scale production functions, the aggregate production function defined by the maximum achievable total output given total inputs is always linear on some part of the domain. Our result provides a microfoundation for the linear production function. |
| Date: | 2023–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2309.15760&r=eff |
| By: | Nilsson, Magnus (CIRCLE, Lund University); Schubert, Torben (CIRCLE, Lund University); Miörner, Johan (CIRCLE, Lund University) |
| Abstract: | This paper analyses the impact of regional anchors on local firms in Swedish regions. Departing from previous idiographic research, we adopt a nomothetic research design relying on a stepwise expert-informed supervised machine learning approach to identify the population of anchor firms in the Swedish economy between 2007 and 2019. We find support for positive anchor effects on the productivity of other firms in the region. These effects are moderated by regional and anchor conditions. We find that the effects are greater when there are multiple anchors within the same industry and that the effects are larger in economically weaker regions. |
| Keywords: | anchor-tenant; productivity; machine learning; anchor firms; Sweden |
| JEL: | D24 O30 R11 R12 |
| Date: | 2023–10–10 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2023_008&r=eff |
| By: | Garcia Suarez, Federico; Perez Quesada, Gabriela |
| Abstract: | Uruguay is a small market with a large export-oriented agribusiness sector. That imposes a challenge for being competitive on the international markets. One of the sectors that is most affected by the international competition is dairy production, where subsidies and market power of large enterprises rules the market. Its main export products are commodities, making it contingent on international prices. Over the years the dairy systems have shifted from an extensive grass-fed model into more intensive farming combining cultivated pastures and larger amounts of high-quality feed. Production saw a maximum in 2013 and a decline since 2014. Another side of this intensification is that as production increases, dairy farms decreases. Between 2011 and 2020 the number of dairy farms dropped 25% while the daily milk production per cow increased more than 50%. Comparing the results of the surveys it seems clear that there are farms running out of business from all sizes, so it is not only a scale issue. This put a question on whether the intensification is sustainable or not and challenge the sector on what are the causes that push farms out of business. To assess these questions, we propose a technical efficiency analysis using two national dairy farm surveys conducted by INALE (Instituto Nacional de Lechería) in 2014 and 2019 using a meta frontier approach to compare the change over time since the surveys are independent and do not compose a panel. The meta frontier allows to compare each survey as a unique group but as of using a technological common source for which a Propensity Score Match is necessary to address biases from observables. From this estimation we can find technical efficiency scores by survey and meta technical efficiency scores that reports the distance to the meta frontier. From that result we can infer if the yield improvement from one survey year to the next is due to movement towards the frontier (improved efficiency) or a productivity improvement due to a shift in the frontier. From the results we expect to provide technology paths that show better performance as possible extension and policy leading recommendations. At this point we are working on the database set up to perform the estimation, so we do not have preliminary results. |
| Keywords: | Livestock Production/Industries, International Relations/Trade |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ags:iaae23:338545&r=eff |
| By: | Tacsir, Ezequiel; Pereira, Mariano |
| Abstract: | This study presents new findings on the impact of the COVID-19 pandemic on productivity and innovation for Caribbean firms, with particular focus on the effects on firm gender diversity and workforce composition. Research on the impact of women's participation on firm performance and innovation has so far produced mixed results, though there is some evidence to suggest that for Latin America, larger shares of women in the knowledge creation and innovation process may increase innovative behavior and, as a consequence, lead to greater labor productivity. In the current context, female participation in firms becomes an even more pressing issue, given the early indications of the pandemics disproportionately negative burden on women s income and jobs in different regions. We found that the gender composition of the personnel has an interesting direct effect on productivity. At the same time, our results show that the expected reductions in female personnel due to the pandemic, have a negative effect in the shares of female participation which, in turn, have the potential to nullify the mentioned productivity channel. This suggests the existence of a minimum threshold of female participation to profit from diversity. Hence, it seems that policy should focus particularly on protecting female jobs, particularly in the wake of dramatic shocks affecting revenues and/or employment. |
| Keywords: | Caribbean;pandemic;innovation;gender;Productivity |
| JEL: | O32 J16 D22 |
| Date: | 2023–03 |
| URL: | http://d.repec.org/n?u=RePEc:idb:brikps:12735&r=eff |
| By: | Mr. Bas B. Bakker |
| Abstract: | This paper addresses the puzzling decline of Total Factor Productivity (TFP) levels in rapidly growing economies, such as Singapore, despite advancements in technology and high GDP per capita growth. The paper proposes that TFP growth is not negative; instead, standard growth decompositions have underestimated TFP growth by overestimating the contribution of capital, failing to account for the substantial part of capital income directed to urban land rents. This leads to an overestimation of changes in capital stock's contribution to growth and thereby an underestimation of TFP growth. A revised decomposition suggests that TFP growth in economies with high land rents and rapid capital stock growth, such as Singapore, has been considerably underestimated: TFP levels have not declined but increased rapidly. |
| Keywords: | Total Factor Productivity; Economic Growth; Capital Stock; Land Rents; Growth Decomposition; Urban Economics; Population Density; Diminishing Returns to Scale; Technological Progress; Singapore; TFP level; re-estimating TFP; land rent; decline of total factor productivity; Capital income; Stocks; Land prices; Asia and Pacific |
| Date: | 2023–08–25 |
| URL: | http://d.repec.org/n?u=RePEc:imf:imfwpa:2023/170&r=eff |
| By: | Flavio Calvino; Luca Fontanelli |
| Abstract: | In this work we characterise French firms using artificial intelligence (AI) and explore the link between AI use and productivity. We relevantly distinguish AI users that source AI from external providers (AI buyers) from those developing their own AI systems (AI developers). AI buyers tend to be larger than other firms, while AI developers are also younger. The share of firms using AI is highest in the ICT sector, which exhibits a particularly high share of developers. Complementary assets, including skills, digital capabilities and infrastructure, play a key role for AI use, with AI buyers and developers leveraging different types of human capital. Overall, AI users tend to be more productive, however this appears largely related to the self-selection of more productive and digital-intensive firms into AI use. This is not the case for AI developers, for which the positive link between AI use and productivity remains evident beyond selection, suggesting a positive effect of AI on their productivity. |
| Keywords: | Technology Diffusion; Artificial Intelligence; Digitalisation; Productivity. |
| Date: | 2023–10–13 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2023/35&r=eff |