Examinando por Autor "Bom, Pedro"
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Ítem ¿Atraerá el BIG- DATA al P-HACKING al mundo de la ingeniería industrial?(Publicaciones DYNA SL, 2019-05) Goti Elordi, Aitor; Bom, Pedro; Campos Granados, José Antonio; Galar-Pascual, DiegoÍtem Fiscal rules and the intergenerational welfare effects of public investment(Elsevier B.V., 2019-09) Bom, PedroA common argument against balanced-budget fiscal rules has it that the costs of durable public capital fall entirely on current generations while its benefits also accrue to future generations. This paper proposes an additional argument whereby balanced-budget rules imply uneven welfare effects of public investment across generations. Using an overlapping generations model of a small open economy, I show that, when subject to a balanced-budget constraint, public investment causes a negative financial wealth effect on current generations. Numerical simulations of the model show that, in terms of welfare, this negative financial wealth effect more than offsets the productivity gains of higher public investment spending, leaving current generations worse-off. A golden rule exempting net public investment from the balanced-budget requirement overturns this effect and allows for welfare gains to both current and future generations. Allowing for debt-financing may thus be necessary to ensure public support for efficient increases in public investment spending.Ítem A generalized-weights solution to sample overlap in meta-analysis(John Wiley and Sons Ltd, 2020-11) Bom, Pedro; Rachinger, HeikoMeta-studies are often conducted on empirical findings obtained from overlapping samples. Sample overlap is common in research fields that strongly rely on aggregated observational data (eg, economics and finance), where the same set of data may be used in several studies. More generally, sample overlap tends to occur whenever multiple estimates are sampled from the same study. We show analytically how failing to account for sample overlap causes high rates of false positives, especially for large meta-sample sizes. We propose a generalized-weights (GW) meta-estimator, which solves the sample overlap problem by explicitly modeling the variance-covariance matrix that describes the structure of dependence among estimates. We show how this matrix can be constructed from information that is usually available from basic sample descriptions in the primary studies (ie, sample sizes and number of overlapping observations). The GW meta-estimator amounts to weighting each empirical outcome according to its share of independent sampling information. We use Monte Carlo simulations to (a) demonstrate how the GW meta-estimator brings the rate of false positives to its nominal level, and (b) quantify the efficiency gains of the GW meta-estimator relative to standard meta-estimators. The GW meta-estimator is fairly straightforward to implement and can solve any case of sample overlap, within or between studies. Highlights: Meta-analyses are often conducted on empirical outcomes based on samples containing common observations. Sample overlap induces a correlation structure among empirical outcomes that harms the statistical properties of meta-analysis methods. We derive the analytic conditions under which sample overlap causes conventional meta-estimators to exhibit high rates of false positives. We propose a generalized-weights (GW) solution to sample overlap, which involves approximating the variance-covariance matrix that describes the correlation structure between outcomes; we show how to construct this matrix from information typically reported in the primary studies. We conduct Monte Carlo simulations to quantify the efficiency gains of the proposed GW estimator and show how it brings the rate of false positives near its nominal level. Although we focus on meta-analyses of regression coefficients, our approach can, in principle, be modified and extended to effect sizes more commonly used in other research fields, such as Cohen's d or odds ratios.Ítem A kinked meta-regression model for publication bias correction(John Wiley and Sons Ltd, 2019-12) Bom, Pedro; Rachinger, HeikoPublication bias distorts the available empirical evidence and misinforms policymaking. Evidence of publication bias is mounting in virtually all fields of empirical research. This paper proposes the endogenous kink (EK) meta-regression model as a novel method of publication bias correction. The EK method fits a piecewise linear meta-regression of the primary estimates on their standard errors, with a kink at the cutoff value of the standard error below which publication selection is unlikely. We provide a simple method of endogenously determining this cutoff value as a function of a first-stage estimate of the true effect and an assumed threshold of statistical significance. Our Monte Carlo simulations show that EK is less biased and more efficient than other related regression-based methods of publication bias correction in a variety of research conditions.Ítem Productive government investment and the labor share(Elsevier Inc., 2022-11) Bom, Pedro; Erauskin Iurrita, IñakiA recent body of literature has sought to determine the causes of the global decline of the labor share. We study the role played by government investment—which has also fallen in many advanced economies over the past few decades—in the labor share decline. We first establish a theoretical link between government investment and the labor share using a general equilibrium macroeconomic model, where government capital enters the production function in a factor-augmenting fashion. Our analytic results show that a permanent cut to government investment causes a steady-state decline in the labor share if the elasticity of substitution between private capital and labor is less than one and public capital augments private capital. We then study the empirical relationship between these variables using two panel datasets covering 79 countries, both developing and developed, over the period 1970–2017. Using a system GMM estimator, we find a positive and statistically significant association between government investment and the labor share in advanced economies; for developing countries, however, we find no effect.Ítem Reporting guidelines for meta-analysis in economics(Blackwell Publishing Ltd, 2020-07) Havránek, Tomáš; Stanley, T. D.; Doucouliagos, Hristos; Bom, Pedro; Geyer-Klingeberg, Jerome; Iwasaki, Ichiro; Reed, W. Robert; Rost, Katja; Aert, R. C. M. vanMeta-analysis has become the conventional approach to synthesizing the results of empirical economics research. To further improve the transparency and replicability of the reported results and to raise the quality of meta-analyses, the Meta-Analysis of Economics Research Network has updated the reporting guidelines that were published by this Journal in 2013. Future meta-analyses in economics will be expected to follow these updated guidelines or give valid reasons why a meta-analysis should deviate from them.