Relevant bibliographies by topics / Olley and Pakes method

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Academic literature on the topic 'Olley and Pakes method'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 February 2022

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Journal articles on the topic "Olley and Pakes method"

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Yasar, Mahmut, Rafal Raciborski, and Brian Poi. "Production Function Estimation in Stata Using the Olley and Pakes Method." Stata Journal: Promoting communications on statistics and Stata 8, no. 2 (2008): 221–31. http://dx.doi.org/10.1177/1536867x0800800204.

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Rovigatti, Gabriele, and Vincenzo Mollisi. "Theory and Practice of Total-Factor Productivity Estimation: The Control Function Approach using Stata." Stata Journal: Promoting communications on statistics and Stata 18, no. 3 (2018): 618–62. http://dx.doi.org/10.1177/1536867x1801800307.

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Alongside instrumental-variables and fixed-effects approaches, the control function approach is the most widely used in production function estimation. Olley and Pakes (1996, Econometrica 64: 1263–1297), Levinsohn and Petrin (2003, Review of Economic Studies 70: 317–341), and Ackerberg, Caves, and Frazer (2015, Econometrica 83: 2411–2451) have all contributed to the field by proposing two-step estimation procedures, whereas Wooldridge (2009, Economics Letters 104: 112–114) showed how to perform a consistent estimation within a single-step generalized method of moments framework. In this article, we propose a new estimator based on Wooldridge's estimation procedure, using dynamic panel instruments à la Blundell and Bond (1998, Journal of Econometrics 87: 115–143), and we evaluate its performance by using Monte Carlo simulations. We also present the new command prodest for production function estimation, and we show its main features and strengths in a comparative analysis with other community-contributed commands. Finally, we provide evidence of the numerical challenges faced when using the Olley–Pakes and Levinsohn–Petrin estimators with the Ackerberg–Caves–Frazer correction in empirical applications, and we document how the generalized method of moments estimates vary depending on the optimizer or starting points used.
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Manjón, Miguel, and Juan Mañez. "Production Function Estimation in Stata Using the Ackerberg–Caves–Frazer Method." Stata Journal: Promoting communications on statistics and Stata 16, no. 4 (2016): 900–916. http://dx.doi.org/10.1177/1536867x1601600406.

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We present a new e-class command, acfest, that implements the method of Ackerberg, Caves, and Frazer (2015, Econometrica 83: 2411–2451) to estimate production functions. This method deals with the functional dependence problems that may arise in the methods proposed by Olley and Pakes (1996, Econometrica 64: 1263–1297) and, particularly, Levinsohn and Petrin (2003, Review of Economic Studies 70: 317–341) (implemented in Stata by Yasar, Raciborski, and Poi [2008, Stata Journal 8: 221–231] and Petrin, Poi, and Levinsohn [2004, Stata Journal 4: 113–123], respectively). In particular, the acfest command yields (nonlinear, robust) generalized method of moments estimates using a Mata function and two specification tests (Wald and Sargan–Hansen). After estimation, predict provides the estimated productivity of the firms in the sample.
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Khac Minh, Nguyen, Phung Mai Lan, and Pham Van Khanh. "Productivity growth and job reallocation in the Vietnamese manufacturing sector." Journal of Economics and Development 21, no. 2 (2019): 172–90. http://dx.doi.org/10.1108/jed-07-2019-0019.

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Purpose The purpose of this paper is to measure TFP growth and job reallocation in the Vietnamese manufacturing industry after the Doimoi period. Design/methodology/approach The study uses firm-level panel data from Vietnam’s annual enterprise survey data for 2000–2016 period in the Vietnamese manufacturing industry using Olley–Pakes static and dynamic productivity decomposition methods. Findings The aggregate productivity estimated from the WRDG method increased 2.323 percent, of which over 40 percent is due to the reallocation toward more productive firms. Olley–Pakes dynamic decomposition according to ownership, scale and industry shows that the contribution of private and state-owned firms and the contribution of small and medium firms and large firms to the TFP growth are 133, −33 percent, 58.56 and 41.44 percent, respectively. The within-firm productivity and net entry components are the main reasons for TFP growth rather than reallocation. The results show that the composition of the aggregate TFPs, estimated from WRDG, OP, LP and ACF, is correlated very high (over 80 percent) except for net entry components. Research limitations/implications The major limitation of this study is that the authors compute an aggregate productivity index using actual employment-based shares (still misallocation in labor), rather than optimal employment-based shares (no misallocation in labor). Originality/value Job reallocation between industries is attracting attention in developing countries, especially transition economies. However, knowledge about job reallocation among industries is limited. This paper assesses the level of job reallocation among private and state-owned firms, small and medium firms and large firms in Vietnam.
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Matsushita, Yukitoshi, and Taisuke Otsu. "LIKELIHOOD INFERENCE ON SEMIPARAMETRIC MODELS WITH GENERATED REGRESSORS." Econometric Theory 36, no. 4 (2019): 626–57. http://dx.doi.org/10.1017/s026646661900029x.

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Hahn and Ridder (2013, Econometrica 81, 315–340) formulated influence functions of semiparametric three-step estimators where generated regressors are computed in the first step. This class of estimators covers several important examples for empirical analysis, such as production function estimators by Olley and Pakes (1996, Econometrica 64, 1263–1297) and propensity score matching estimators for treatment effects by Heckman, Ichimura, and Todd (1998, Review of Economic Studies 65, 261–294). The present article studies a nonparametric likelihood-based inference method for the parameters in such three-step estimation problems. In particular, we apply the general empirical likelihood theory of Bravo, Escanciano, and van Keilegom (2018, Annals of Statistics, forthcoming) to modify semiparametric moment functions to account for influences from plug-in estimates into the above important setup, and show that the resulting likelihood ratio statistic becomes asymptotically pivotal without undersmoothing in the first and second step nonparametric estimates.
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Liu, Wenjun, Tomokazu Nomura, and Shoji Nishijima. "Gender discrimination and firms’ profit: evidence from Brazil." Journal of Economic Studies 43, no. 5 (2016): 801–14. http://dx.doi.org/10.1108/jes-06-2014-0093.

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Purpose This paper investigates discrimination against women within the Brazilian labour market using firm-level data from the World Bank Investment Climate Survey. The purpose of this paper is to determine whether the female employees in the Brazilian labour market are paid less than their productivity warrants due to the existence of discrimination. Design/methodology/approach Based on employer discrimination model proposed by Becker (1971) that considered the proportion of female employees as a proxy for the extent of discrimination, the authors estimate the profit function using OLS analysis, and regress it on the proportion of female employees and other firm characteristics. To address the endogeneity problem caused by unobservable productivity shocks, the authors employed the methods proposed by Olley and Pakes (1996) and Levinsohn and Petrin (2003), respectively. Findings The results indicate that the proportion of female employees has positive effect on firms’ profit in 2002, but has no effect in 2007. This finding gives evidence of the existence of discrimination against female employees within the Brazilian labour market in the early 2000s, while the gender discrimination was reduced overtime. Originality/value This paper’s main contribution is to provide an approach that differs from that of previous research to determine whether discrimination exists within the Brazilian labour market. This paper also provides policy insights for Brazilian labour market.
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Hyytinen, Ari, Pekka Ilmakunnas, and Mika Maliranta. "Olley-Pakes productivity decomposition: computation and inference." Journal of the Royal Statistical Society: Series A (Statistics in Society) 179, no. 3 (2015): 749–61. http://dx.doi.org/10.1111/rssa.12135.

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Melitz, Marc J., and Sašo Polanec. "Dynamic Olley-Pakes productivity decomposition with entry and exit." RAND Journal of Economics 46, no. 2 (2015): 362–75. http://dx.doi.org/10.1111/1756-2171.12088.

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Lee, Yoonseok, Andrey Stoyanov, and Nikolay Zubanov. "Olley and Pakes-style Production Function Estimators with Firm Fixed Effects." Oxford Bulletin of Economics and Statistics 81, no. 1 (2018): 79–97. http://dx.doi.org/10.1111/obes.12259.

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Maliranta, Mika, and Niku Määttänen. "An Augmented Static Olley-Pakes Productivity Decomposition with Entry and Exit: Measurement and Interpretation." Economica 82 (August 6, 2015): 1372–416. http://dx.doi.org/10.1111/ecca.12159.

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Dissertations / Theses on the topic "Olley and Pakes method"

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Rocha, Sálvio Pontes Moreira. "Uma estimativa da função de produção no setor sucroalcooleiro utilizando microdados de custo." reponame:Repositório Institucional do FGV, 2013. http://hdl.handle.net/10438/11203.

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Productivity is often calculated by the approach of the Cobb-Douglas production function. This estimate, however, may suffer from s imultaneity and inputs bias selection. The method of Olley and Pakes (1996) int roduced a semi-parametric method allows us to estimate the parameters of the production function consistently and thus obtain reliable measures of p roductivity, controlling such bias problems. This study applies this method in a company the sugarcane sector and uses the command opreg at Stata to esti mate the production function of a company and concluded with the econom ic intuition behind the result.
Produtividade é frequentemente calculada pela aproximação da função de produção Cobb-Douglas. Tal estimativa, no entanto, pode sofrer de simultaneidade e viés de seleção dos insumos. Olley e Pakes (1996) introduziu um método semi-paramétrico que nos permite estimar os parâmetros da função de produção de forma consistente e, assim, obter medidas de produtividade confiável, controlando tais problemas de viés. Este estudo aplica este método em uma empresa do setor sucroalcooleiro e utiliza o comando opreg do Stata com a finalidade de estimar a função produção, descrevendo a intuição econômica por trás dos resultados.
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Kosteas, Billy D. "The impact of foreign direct investment and trade policy on productivity, wages and technology adoption in Mexican manufacturing plants." Connect to this title online, 2004. http://bibpurl.oclc.org/web/21104.

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Book chapters on the topic "Olley and Pakes method"

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Karagiannis, Giannis, and Suzanna M. Paleologou. "Exploring the Covariance Term in the Olley-Pakes Productivity Decomposition." In Productivity and Inequality. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-68678-3_8.

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Reports on the topic "Olley and Pakes method"

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Melitz, Marc, and Sašo Polanec. Dynamic Olley-Pakes Productivity Decomposition with Entry and Exit. National Bureau of Economic Research, 2012. http://dx.doi.org/10.3386/w18182.

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