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on Efficiency and Productivity |
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Issue of 2024‒04‒01
eleven papers chosen by |
| By: | Fernando M. Aragon; Diego Restuccia; Juan Pablo Rud |
| Abstract: | We examine empirically whether the level of data aggregation affects the assessment of misallocation in agriculture. Using data from Ugandan farmers, we document a substantial discrepancy between misallocation measures calculated at the plot and at the farm levels. Estimates of misallocation at the plot level are much higher than those estimated with the same data but aggregated at the farm level. Even after accounting for measurement error and unobserved heterogeneity, estimates of misallocation at the plot level are extremely high, with nationwide agricultural productivity gains of 562%. Furthermore, we find suggestive evidence that granular data may be more susceptible to measurement error in survey data and that data aggregation can attenuate the relative magnitude of measurement error in misallocation measures. Our findings suggest caution in generalizing insights on measurement error and misallocation from plot-level analysis to those at the farm level. |
| Keywords: | misallocation, agriculture, measurement error, distortions. |
| JEL: | O4 O13 Q12 |
| Date: | 2024–02–20 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-769&r=eff |
| By: | Victor Ajayi; Michael G. Pollitt |
| Keywords: | Green growth, net zero, circular economy, future energy scenarios, productivity |
| JEL: | D24 O44 Q53 Q54 |
| Date: | 2022–10 |
| URL: | http://d.repec.org/n?u=RePEc:enp:wpaper:eprg2215&r=eff |
| By: | Berlingieri, Giuseppe; Blanchenay, Patrick; Criscuolo, Chiara |
| Abstract: | This paper provides new evidence on the increasing dispersion in wages and productivity using a unique micro-aggregated firm-level data source, representative for the full population of firms in 12 countries. First, we document an increase in wage and productivity dispersions, for both manufacturing and market services, and show that the increase is mainly driven by the bottom of the wage and productivity distributions. Second, we show that between-firm wage dispersion increased more in sectors that experienced an increase in productivity dispersion; the estimated elasticity is larger at the bottom than at the top of the wage/productivity distributions, consistent with a framework in which more productive firms charge higher mark-ups and/or larger wage mark-downs. Third, we find that both globalisation and digitalisation strengthen the link between productivity and wage dispersion. Our results suggest that policies designed to mitigate wage inequality must take into consideration gaps between firms of the same sectors, and how both globalisation and digitalisation affect these gaps. |
| Keywords: | digitalisation; dispersion; globalisation; productivity; wages |
| JEL: | J50 |
| Date: | 2024–04–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:122046&r=eff |
| By: | David Kreitmeir; Paul A. Raschky |
| Abstract: | We analyse the individual productivity effects of Italy's ban on ChatGPT, a generative pretrained transformer chatbot. We compile data on the daily coding output quantity and quality of over 36, 000 GitHub users in Italy and other European countries and combine these data with the sudden announcement of the ban in a difference-in-differences framework. Among the affected users in Italy, we find a short-term increase in output quantity and quality for less experienced users and a decrease in productivity on more routine tasks for experienced users. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.01964&r=eff |
| By: | Xiaodong Zhu |
| Abstract: | Total factor productivity (TFP) growth has been the primary driver of China's GDP growth. From 1978 to 2007, China experienced an average TFP growth rate of over 4% per year, thanks to economic reforms and decentralization that led to consistent policy and institutional changes initiated from local levels. However, since 2007, the Chinese government has shifted towards a top-down approach, prioritizing policy design at the national level and resource mobilization. While this approach yielded some short-term benefits, such as temporary growth recovery in 2010 following the global financial crisis and the rapid expansion of infrastructure projects, it came at a significant cost to economic efficiency. Without comprehensive bottom-up policy reforms, China's TFP growth rate between 2007 and 2022 averaged only 1% per year, significantly lower than the 4% achieved prior to 2007. The key challenge facing China now is whether it will revert to a decentralized decision-making process. |
| Keywords: | China, Bottom-up Institutional Change, TFP, Growth, Centralization, Growth Slowdown |
| JEL: | O1 O4 O5 |
| Date: | 2024–03–13 |
| URL: | http://d.repec.org/n?u=RePEc:tor:tecipa:tecipa-771&r=eff |
| By: | Ernst, Ekkehard,; Langot, François,; Merola, Rossana,; Tripier, Fabien, |
| Abstract: | Out of four major structural changes affecting the US economy – namely a rising share of skilled workers, skill-biased technological change, decreasing progressiveness of taxation and productivity slowdown – we show that the decline in productivity growth not only is the main driver of the widening wealth disparities observed in the United States of America over the past few decades, but is also the only mechanism that can explain inequalities both within and between skill groups. |
| Keywords: | wealth, economic disparity |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ilo:ilowps:995353092902676&r=eff |
| By: | Elizabeth Steiner |
| Abstract: | This paper estimates the impact of exchange rate fluctuations on markups. Firm-level markups are estimated for a comprehensive panel of Swiss manufacturing firms for the period 2012-2017 using a production-function approach. The pass-through of the exchange rate is then estimated using an event-study design exploiting the large, sudden and persistent appreciation of the Swiss franc against the euro in January 2015. The results show that following an appreciation, Swiss manufacturing firms adjust their markup very heterogeneously. Large firms, especially those that invoice in foreign currency or are highly profitable, substantially decrease their markup. Owing to their sheer size, large firms shape the aggregate response. In contrast, the average firm does not respond significantly. This suggests that smaller firms, which are in the majority, are either unable or unwilling to absorb exchange rate movements by adjusting their markup. |
| Keywords: | Markup, Exchange rate, Pass-through, Firm-level data |
| JEL: | D22 D24 F12 F14 F41 F23 L11 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:snb:snbwpa:2024-02&r=eff |
| By: | Voraprapa Nakavachara; Tanapong Potipiti; Thanee Chaiwat |
| Abstract: | Generative AI technologies such as ChatGPT, Gemini, and MidJourney have made remarkable progress in recent years. Recent literature has documented ChatGPT's positive impact on productivity in areas where it has strong expertise, attributable to extensive training datasets, such as the English language and Python/SQL programming. However, there is still limited literature regarding ChatGPT's performance in areas where its capabilities could still be further enhanced. This paper aims to fill this gap. We conducted an experiment in which economics students were asked to perform writing analysis tasks in a non-English language (specifically, Thai) and math & data analysis tasks using a less frequently used programming package (specifically, Stata). The findings suggest that, on average, participants performed better using ChatGPT in terms of scores and time taken to complete the tasks. However, a detailed examination reveals that 34% of participants saw no improvement in writing analysis tasks, and 42% did not improve in math & data analysis tasks when employing ChatGPT. Further investigation indicated that higher-ability students, as proxied by their econometrics grades, were the ones who performed worse in writing analysis tasks when using ChatGPT. We also found evidence that students with better digital skills performed better with ChatGPT. This research provides insights on the impact of generative AI. Thus, stakeholders can make informed decisions to implement appropriate policy frameworks or redesign educational systems. It also highlights the critical role of human skills in addressing and complementing the limitations of technology. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.01770&r=eff |
| By: | He, Zhiguo (U of Chicago); Liao, Guanmin (Renmin U of China); Wang, Baolian (U of Florida) |
| Abstract: | We study the impact of government-led incentive systems by examining a staggered reform in the Chinese state-owned enterprise (SOE) performance evaluation policy. To improve capital allocative efficiency, regulators switched from using return on equity (ROE) to economic value added (EVA). However, this EVA policy takes a one-size-fits-all approach by stipulating a fixed cost of capital for virtually all SOEs, neglecting the potential heterogeneity of firm-specific costs of capital. We show that SOEs responded to the evaluation reform by altering their investment decisions, particularly when the actual borrowing rate deviated further from the stipulated rate. Besides providing an estimate of the cost of capital's impact on investment, our paper offers causal evidence that incentive schemes affect real investment and sheds new light on economic reform challenges in China. |
| JEL: | G31 G34 M12 M52 P31 |
| Date: | 2023–08 |
| URL: | http://d.repec.org/n?u=RePEc:ecl:stabus:4135&r=eff |
| By: | Sezer, Ayse Hazal (Tilburg University, Center For Economic Research); Uras, Burak (Tilburg University, Center For Economic Research) |
| Keywords: | Firm Size; Productivity; Wages; Scalability; Industry Dynamics; Automation; Unions |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:tiu:tiucen:81a58c37-dd82-442d-aab1-b27f70a22ba1&r=eff |
| By: | Donghoon Lee; Anirban Basu; Jerome A. Dugan; Pinar Karaca-Mandic |
| Abstract: | The paper examines whether, among inpatient psychiatric admissions in California, for-profit (FP) hospitals engage in cream skimming, i.e., choosing patients for some characteristic(s) other than their need for care, which enhances the profitability of the provider. We propose a novel approach to identify cream skimming using cost outcomes. Naïve treatment effect estimates of hospital ownership type consist of the impact of differential patient case mix (selection) and hospital cost containment strategies (execution). In contrast, an instrumental variable (IV) approach can control for case mix and establish the causal effects of ownership type due to its execution. We interpret the difference in naïve and IV treatment effects to be driven by FP hospitals’ selection (cream skimming) based on unobserved patient case mix. We find that FP hospitals are more likely to treat high-cost patients than not-for-profit (NFP) hospitals, showing no evidence that FP hospitals engage in cream skimming. Our results may alleviate concerns surrounding the recent proliferation of FP psychiatric hospitals with regards to cream skimming. |
| JEL: | I10 I18 L31 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32179&r=eff |