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on Efficiency and Productivity |
| By: | Florens, Jean-Pierre; Fève, Frédérique; Simar, Léopold |
| Abstract: | The analysis of cost functions is an important topic in econometrics both for scientific studies and for industrial applications. The object of interest may be the cost of a firm or the cost of a specific production, in particular in case of a proposal to a procurement. Engineer methods evaluate the technical cost given the main characteristics of the output using the decomposition of the production process in elementary tasks and are based on physical laws. The error terms in these models may be viewed as idiosyncratic chocs. The economist usually observes ex post the cost and the characteristics of the product. The difference between theoretical cost and the observed one may be modeled by the inefficiency of the production process. In this case, econometric models are cost frontier models. In this paper we propose to take advantage of the situation where we have information from both approaches. We consider a system of two equations, one being a standard regression model (for the technical cost function) and one being a stochastic frontier model for the economic cost function where inefficiencies are explicitly introduced. We derive estimators of this joint model and derive its asymptotic properties. The models are presented in classical parametric approach, with few assumptions on the stochastic properties of the joint error terms. We suggest also a way to extend the model to a nonparametric approach, the latter provides an original way to model and estimate nonparametric stochastic frontier models. The techniques are illustrated in the case of the cost function for the distribution of gas in France. |
| Date: | 2025–05–19 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130551 |
| By: | Vittorio Bassi; Jung Hyuk Lee; Alessandra Peter; Tommaso Porzio; Ritwika Sen; Esau Tugume |
| Abstract: | We study the internal organization of manufacturing firms in Uganda. We measure what people do within firms and find limited specialization, far below what is feasible given the prevailing production process and average firm size of 5.7 workers. We build and estimate an occupational choice model in which firm size, productivity, and specialization arise endogenously. The model shows that firms in this setting are largely “self-employment in disguise” and generate just a 20% productivity gain over literal self-employment. In a counterfactual economy with full specialization, the same aggregate output can be produced with an average firm size of only 1.6. |
| JEL: | O11 O17 L23 L25 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11900 |
| By: | Andrew J. Fieldhouse; Karel Mertens |
| Abstract: | Recent empirical evidence by Fieldhouse and Mertens (2024) points to a strong causal link between federal nondefense R&D funding and private-sector productivity growth, and large implied social returns to public R&D investment. We show that these high social return estimates broadly align with existing evidence on the social returns to private or total R&D spending. If the R&D increases authorized under the CHIPS and Science Act were fully appropriated, our modeling indicates a boost in U.S. productivity within a few years, reaching gains of 0.2–0.4% after seven years or more. At their peak, the direct productivity effects of the implied expansion in nondefense R&D alone would raise output by over $40 billion in a single year—exceeding total outlays from the CHIPS Act R&D provisions over a decade. The potential productivity impact of fiscal consolidations changing R&D spending is not clear ex ante. We show that in recent fiscal consolidations, cuts to federal R&D funding were largely borne by defense R&D, whereas funding for nondefense R&D was largely spared or was increased. Our evidence suggests that future deficit reduction efforts that instead emphasize cuts to nondefense R&D funding could have a larger adverse impact on productivity and economic growth than previous fiscal consolidations. |
| Keywords: | Public R&D; productivity; growth; innovation; fiscal consolidations |
| JEL: | E62 O38 O47 |
| Date: | 2025–05–14 |
| URL: | https://d.repec.org/n?u=RePEc:fip:feddwp:99990 |
| By: | Rouvinen, Petri; Kässi, Otto; Pajarinen, Mika |
| Abstract: | Abstract Finland’s future prosperity hinges on intangible assets such as software, data, brands, and organizational capital. While research and development (R&D) is a central intangible asset, other types collectively hold greater significance. The growth trajectory of Finland’s intangible investments stalled with the 2008–2009 financial crisis and resumed only after the COVID-19 pandemic. This “lost decade” partly explains Finland’s sluggish economic and productivity performance. Innovation policy should broaden its focus beyond R&D to encompass other forms of intangible investment, as well as the adoption and diffusion of innovations. Policy should prioritize quality over quantity, encourage bold experimentation, and support scaling. This necessitates a shift towards equity financing and fostering skilled labor mobility. Mergers and acquisitions are vital for leveraging and disseminating intangible capital, but anti-competitive “killer acquisitions” are not in the national interest. |
| Keywords: | Intangible capital, Investments, Productivity, Innovation policy, Economic growth, Spillovers |
| JEL: | D24 E22 G32 O34 |
| Date: | 2025–06–05 |
| URL: | https://d.repec.org/n?u=RePEc:rif:report:164 |
| By: | Andrew J. Fieldhouse; Karel Mertens |
| Abstract: | Recent empirical evidence by Fieldhouse and Mertens (2024) points to a strong causal link between federal nondefense R&D funding and private-sector productivity growth, and large implied social returns to public R&D investment. We show that these high social return estimates broadly align with existing evidence on the social returns to private or total R&D spending. If the R&D increases authorized under the CHIPS and Science Act were fully appropriated, our modeling indicates a boost in U.S. productivity within a few years, reaching gains of 0.2–0.4% after seven years or more. At their peak, the direct productivity effects of the implied expansion in nondefense R&D alone would raise output by over $40 billion in a single year—exceeding total outlays from the CHIPS Act R&D provisions over a decade. The potential productivity impact of fiscal consolidations changing R&D spending is not clear ex ante. We show that in recent fiscal consolidations, cuts to federal R&D funding were largely borne by defense R&D, whereas funding for nondefense R&D was largely spared or was increased. Our evidence suggests that future deficit reduction efforts that instead emphasize cuts to nondefense R&D funding could have a larger adverse impact on productivity and economic growth than previous fiscal consolidations. |
| JEL: | E6 O38 O47 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33780 |
| By: | J. Scott Holladay (Department of Economics, University of Tennessee, Fellow, Howard B. Baker School for Public Policy); Justin R. Roush (Department of Economics, Xavier University) |
| Abstract: | We document significant variation in the relative pollution emissions of foreign owned and domestically owned manufacturing plants in the U.S. We use a sample of matched plant characteristics and pollution emissions to document the pollution emissions of foreign owned facilities relative to their competitors in the same industry. On average there is no difference in emissions intensity between domestic and foreign owned plants across all manufacturers, but in some industries foreign owned plants are much cleaner, while in others much dirtier. We show that the variation in relative pollution emissions of foreign owned manufacturing plants is correlated with industry characteristics: lower industry-level trade costs, higher fixed costs, and lower returns to agglomeration are associated with cleaner foreign owned plants. These results are consistent with a theoretical framework in which foreign plants have lower productivity, and therefore more pollution intensity, in industries where foreign ownership is more attractive relative to exporting. |
| Keywords: | Trade and environment, Firm heterogeneity, Plant-level emissions |
| JEL: | F1 Q5 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:ten:wpaper:2025-02 |
| By: | Frédéric Vinas |
| Abstract: | I study the impact of oil price shocks to non-financial firms over two decades using a highly granular firm-level dataset. I show the impact of these price shocks to key financial and operational metrics, including value added, employment, real wages, labor share, profit margins, dividend payments, productivity, and credit risk. I highlight the asymmetric effects of oil price increases and decreases. A one standard deviation increase in the weighted oil price shocks leads to a €396 decrease in per capita productivity (in 2024 euros), and a 0.30 percentage point increase in the probability of default, while there is no significant effect in the case of oil price decreases, leading to persistent effects of oil price increases in the medium term. I also show heterogeneous effects of oil price increases across firm size and energy intensity. This paper has implications for policymakers, especially those concerned with financial stability (bank stress-testing, climate stress-testing, macro-financial modeling), and competitiveness, and more generally for those studying climate transition risks. |
| Keywords: | Oil Shock, Oil Price, Raw Materials, Value Added, Wage Bill, Labor Share, Profit Margin, Default, Productivity, Climate Risk, Transition Risk, Physical Risk, Credit Risk |
| JEL: | D33 E32 G3 G33 G35 Q41 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:bfr:banfra:989 |
| By: | Gholamreza Hajargasht (Griffith University); Alicia Rambaldi (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia); D.S. Prasada Rao (School of Economics and Centre for Efficiency and Productivity Analysis (CEPA) at The University of Queensland, Australia) |
| Abstract: | Convergence in incomes, productivity-catch-up and technology gaps have been studied extensively. This study focuses on convergence in income and income distributions, two factors that determine welfare. The paper offers an intuitive notion of income convergence which is then used in establishing an analytical link between income (sigma) convergence and inequality measures. Empirical results reported are based on data series available from UQICD V3.0 (University of Queensland International Comparison Database) covering 185 countries and the period 1970 to 2019 covering pre- and post-globalization years. Using recently developed econometric methods, the paper finds strong evidence of weak-sigma convergence, absolute and conditional convergence; as well as convergence tested using economic transition curves proposed in Phillips and Sul (2009). However, the results vary depending on the groups of countries considered with robust results for the group of countries classified as the upper-middle income group. World inequality, accounting for income distributions within countries, peaked during 1990 to 1995 with a Gini coefficient around 0.72 decreasing to 0.575 by 2019. There is evidence of a reduction in between- country inequality coupled with a rise in within-country inequality. The paper proposes a new entropy-based measure of divergence between income distributions. Under Pareto-lognormal specification, fitted income distributions for a large number of countries for years between 1970 and 2019, available from the UQICD database, show a significant reduction in divergence in income distribution of countries in the world from 1985 to around 2015 but increasingly slightly until 2019. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:qld:uqcepa:197 |
| By: | Yu Hao; Hiroyuki Kasahara |
| Abstract: | This paper develops statistical methods for determining the number of components in panel data finite mixture regression models with regression errors independently distributed as normal or more flexible normal mixtures. We analyze the asymptotic properties of the likelihood ratio test (LRT) and information criteria (AIC and BIC) for model selection in both conditionally independent and dynamic panel settings. Unlike cross-sectional normal mixture models, we show that panel data structures eliminate higher-order degeneracy problems while retaining issues of unbounded likelihood and infinite Fisher information. Addressing these challenges, we derive the asymptotic null distribution of the LRT statistic as the maximum of random variables and develop a sequential testing procedure for consistent selection of the number of components. Our theoretical analysis also establishes the consistency of BIC and the inconsistency of AIC. Empirical application to Chilean manufacturing data reveals significant heterogeneity in production technology, with substantial variation in output elasticities of material inputs and factor-augmented technological processes within narrowly defined industries, indicating plant-specific variation in production functions beyond Hicks-neutral technological differences. These findings contrast sharply with the standard practice of assuming a homogeneous production function and highlight the necessity of accounting for unobserved plant heterogeneity in empirical production analysis. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.09666 |