scholarly journals Non-Neutral Marginal Innovation Costs, Omitted Variables, and Induced Innovation

2020 ◽  
Vol 49 (3) ◽  
pp. 465-491
Author(s):  
Daegoon Lee ◽  
Benjamin W. Cowan ◽  
C. Richard Shumway
Keyword(s):  
Fixed Effects ◽  
Test Procedure ◽  
Model Specification ◽  
Supply Side ◽  
Public Research ◽  
Omitted Variables ◽  
Induced Innovation ◽  
Research Expenditures ◽  
Fixed Effects Estimator ◽  
Research Cost

Prior tests of Hicks’ Induced Innovation Hypothesis (IIH) have been greatly hampered because the lack of supply-side data implicitly requires the untenable assumption that the marginal research cost is the same for different inputs. We document that, with appropriate model specification and panel data, a two-way fixed-effects estimator can account for much of the non-neutrality of the innovation function. Using a test procedure that is robust to a time-variant and non-neutral innovation function, we test the IIH in U.S. agriculture for the period 1960–2004. We use only readily available data for innovation demand and total public research expenditures.

scholarly journals Not so Harmless After All: The Fixed-Effects Model

2018 ◽  
Vol 27 (1) ◽  
pp. 21-45 ◽  
Author(s):  
Thomas Plümper ◽  
Vera E. Troeger
Keyword(s):  
Model Selection ◽  
Fixed Effects ◽  
Time Varying ◽  
Multiple Model ◽  
Fixed Effects Model ◽  
Omitted Variables ◽  
Hausman Test ◽  
Fixed Effects Estimator ◽  
Time Invariant

The fixed-effects estimator is biased in the presence of dynamic misspecification and omitted within variation correlated with one of the regressors. We argue and demonstrate that fixed-effects estimates can amplify the bias from dynamic misspecification and that with omitted time-invariant variables and dynamic misspecifications, the fixed-effects estimator can be more biased than the ‘naïve’ OLS model. We also demonstrate that the Hausman test does not reliably identify the least biased estimator when time-invariant and time-varying omitted variables or dynamic misspecifications exist. Accordingly, empirical researchers are ill-advised to rely on the Hausman test for model selection or use the fixed-effects model as default unless they can convincingly justify the assumption of correctly specified dynamics. Our findings caution applied researchers to not overlook the potential drawbacks of relying on the fixed-effects estimator as a default. The results presented here also call upon methodologists to study the properties of estimators in the presence of multiple model misspecifications. Our results suggest that scholars ought to devote much more attention to modeling dynamics appropriately instead of relying on a default solution before they control for potentially omitted variables with constant effects using a fixed-effects specification.

What Goes Up Might Not Come Down: Modeling Directional Asymmetry with Large-N, Large-T Data

2021 ◽  
pp. 008117502110463
Author(s):  
Ryan P. Thombs ◽  
Xiaorui Huang ◽  
Jared Berry Fitzgerald
Keyword(s):  
Fixed Effects ◽  
Directional Asymmetry ◽  
Cross Sectional ◽  
Monte Carlo Experiments ◽  
Long Run ◽  
Large N ◽  
Fixed Effects Estimator ◽  
Cross Sectional Dependence ◽  
Using Data ◽  
Heterogeneous Panel

Modeling asymmetric relationships is an emerging subject of interest among sociologists. York and Light advanced a method to estimate asymmetric models with panel data, which was further developed by Allison. However, little attention has been given to the large- N, large- T case, wherein autoregression, slope heterogeneity, and cross-sectional dependence are important issues to consider. The authors fill this gap by conducting Monte Carlo experiments comparing the bias and power of the fixed-effects estimator to a set of heterogeneous panel estimators. The authors find that dynamic misspecification can produce substantial biases in the coefficients. Furthermore, even when the dynamics are correctly specified, the fixed-effects estimator will produce inconsistent and unstable estimates of the long-run effects in the presence of slope heterogeneity. The authors demonstrate these findings by testing for directional asymmetry in the economic development–CO2 emissions relationship, a key question in macro sociology, using data for 66 countries from 1971 to 2015. The authors conclude with a set of methodological recommendations on modeling directional asymmetry.

scholarly journals The impact of public research expenditure on agricultural productivity: evidence from developed European countries

2021 ◽  
pp. 55-60
Author(s):  
Alessandro Magrini
Keyword(s):  
United States ◽  
Fixed Effects ◽  
Agricultural Research ◽  
Agricultural Productivity ◽  
European Countries ◽  
United States Department ◽  
Public Research ◽  
Food And Agriculture Organization ◽  
The Impact ◽  
Research Expenditure

The objective of this paper is to assess the impact of public research expenditure on agricultural productivity in developed European countries. Our research provides original evidence, making possible a comparison with existing studies focused on United States of America (USA). We apply a fixed effects Gamma distributed-lag model to yearly data in 1970-2016 sourced from the United States Department of Agriculture (USDA), the Organisation for Economic Cooperation and Development (OECD), and the Food and Agriculture Organization (FAO). In our results, public research expenditure has a significant impact on agricultural productivity up to 35 years, with peak at 17 years and long-term elasticity equal to 0.172. Based on our model, the countries with the highest internal rate of return of agricultural research expenditure resulted Germany, Spain, France and Italy (24.5-25.2%), followed by Netherlands, United Kingdom, Denmark, Greece, Belgium and Luxembourg (20.5-21.8%). However, only Germany, Denmark and Greece increased agricultural research expenditure in recent years. The estimated internal rates of return are in line with the ones reported by existing studies on USA, and they suggest that developed European countries, just like USA, could benefit from research investments in Agriculture to a much greater extent than they currently do.

scholarly journals Board gender diversity and environmental, social and governance performance of US banks: moderating role of environmental, social and corporate governance controversies

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammad Hassan Shakil ◽  
Mashiyat Tasnia ◽  
Md Imtiaz Mostafiz
Keyword(s):  
Corporate Governance ◽  
Fixed Effects ◽  
Resource Dependence ◽  
Gender Diversity ◽  
Corporate Boards ◽  
Omitted Variables ◽  
Content Type ◽  
Dynamic Panel Regression ◽  
Board Gender Diversity

PurposeGender diversity in corporate boards is broadly studied in existing corporate governance literature. However, the role of board gender diversity on environmental, social and governance (ESG) performance of the banks is still unaccounted for. Drawing on resource dependence and legitimacy theory, this study addresses this pressing research issue. Moreover, investigation of ESG controversies as a moderator paves the existing corporate governance research to the new avenues.Design/methodology/approachData were sourced from Refinitiv database on 37 US banks from the period of 2013 to 2017. This study employs static and dynamic panel regression models that include random effects, fixed effects and dynamic generalised method of moments (GMMs) to test the hypotheses. Furthermore, system GMM is used to reduce the issue of endogeneity, measurement error, omitted variables bias and bank-specific heterogeneity.FindingsWe identify a significant positive relationship between board gender diversity and the ESG performance of US banks. However, the result propounds non-significant moderating effect of ESG controversies on the board gender diversity–ESG performance nexus.Originality/valueLiterature on board gender diversity and ESG separately and predominantly explains firm/bank's financial performance. This study is one of the pioneering attempts to explain the role of board gender diversity on ESG performance. Although incremental, however, this study also contributes to the literature on ESG in the US context.

scholarly journals Estimation of Nonstationary Heterogeneous Panels

2007 ◽  
Vol 7 (2) ◽  
pp. 197-208 ◽  
Author(s):  
Edward F. Blackburne ◽  
Mark W. Frank
Keyword(s):  
Time Series ◽  
Fixed Effects ◽  
American Statistical Association ◽  
Statistical Association ◽  
Pooled Mean Group ◽  
Long Run ◽  
Fixed Effects Estimator ◽  
The Mean ◽  
Pooled Mean Group Estimator ◽  
Heterogeneous Panels

We introduce a new Stata command, xtpmg, for estimating nonstationary heterogeneous panels in which the number of groups and number of time-series observations are both large. Based on recent advances in the nonstationary panel literature, xtpmg provides three alternative estimators: a traditional fixed-effects estimator, the mean-group estimator of Pesaran and Smith (Estimating long-run relationships from dynamic heterogeneous panels, Journal of Econometrics 68: 79–113), and the pooled mean-group estimator of Pesaran, Shin, and Smith (Estimating long-run relationships in dynamic heterogeneous panels, DAE Working Papers Amalgamated Series 9721; Pooled mean group estimation of dynamic heterogeneous panels, Journal of the American Statistical Association 94: 621–634).

scholarly journals Technical Efficiency and Technical Change in Canadian Manufacturing Industries

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Samuel Gamtessa
Keyword(s):  
Technical Efficiency ◽  
Technical Change ◽  
Fixed Effects ◽  
Manufacturing Sector ◽  
Stochastic Frontier ◽  
Manufacturing Industries ◽  
Omitted Variables ◽  
Dynamic Panel ◽  
Data Set ◽  
Canadian Manufacturing

This study applies the “true fixed effects” panel stochastic frontier methodology to the Canadian KLEMS data set to estimate technical change and technical efficiency in the Canadian manufacturing sector. To account for the endogeneity of capital inputs as well as the possible problems related to omitted variables, a two-stage residual inclusion method is pursued. The first stage is estimated using the dynamic panel GMM method. The results show that Canadian manufacturing industries experienced significant declines in technical efficiencies during the last ten years. This suggests that the observed slowdown in TFP growth during the recent past is partly due to declining technical efficiency.

PANEL DATA MODELS WITH FINITE NUMBER OF MULTIPLE EQUILIBRIA

2009 ◽  
Vol 26 (3) ◽  
pp. 863-881 ◽  
Author(s):  
Jinyong Hahn ◽  
Hyungsik Roger Moon
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Multiple Equilibria ◽  
Finite Sample ◽  
Finite Support ◽  
Time Dimension ◽  
Cross Sectional ◽  
Incidental Parameters ◽  
Cross Sectional Dimension ◽  
Fixed Effects Estimator

We study a nonlinear panel data model in which the fixed effects are assumed to have finite support. The fixed effects estimator is known to have the incidental parameters problem. We contribute to the literature by making a qualitative observation that the incidental parameters problem in this model may not be not as severe as in the conventional case. Because fixed effects have finite support, the probability of correctly identifying the fixed effect converges to one even when the cross sectional dimension grows as fast as some exponential function of the time dimension. As a consequence, the finite sample bias of the fixed effects estimator is expected to be small.

Religious Minorities and Resistance to Genocide: The Collective Rescue of Jews in the Netherlands during the Holocaust

2016 ◽  
Vol 110 (1) ◽  
pp. 127-147 ◽  
Author(s):  
ROBERT BRAUN
Keyword(s):  
The Netherlands ◽  
Fixed Effects ◽  
Minority Groups ◽  
Local Level ◽  
Spatial Regression ◽  
Omitted Variables ◽  
Religious Minority ◽  
Protestant Churches ◽  
Local Configuration ◽  
The Holocaust

This article hypothesizes that minority groups are more likely to protect persecuted groups during episodes of mass killing. The author builds a geocoded dataset of Jewish evasion and church communities in the Netherlands during the Holocaust to test this hypothesis. Spatial regression models of 93 percent of all Dutch Jews demonstrate a robust and positive correlation between the proximity to minority churches and evasion. While proximity to Catholic churches increased evasion in dominantly Protestant regions, proximity to Protestant churches had the same effect in Catholic parts of the country. Municipality level fixed effects and the concentric dispersion of Catholicism from missionary hotbed Delft are exploited to disentangle the effect of religious minority groups from local level tolerance and other omitted variables. This suggests that it is the local configuration of civil society that produces collective networks of assistance to threatened neighbors.

Local Semi-Parametric Efficiency of the Poisson Fixed Effects Estimator

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Valentin Verdier
Keyword(s):  
Count Data ◽  
Fixed Effects ◽  
Econometric Models ◽  
Fixed Effects Estimator

AbstractHausman, Hall, and Griliches [Hausman, J., H. B. Hall, and Z. Griliches. 1984. “Econometric Models for Count Data with an Application to the Patents-R & D Relationship.”

scholarly journals Public expenditures and the production of education

2016 ◽  
Vol 24 ◽  
pp. 88
Author(s):  
Stephen R. Neely ◽  
Jeffrey Diebold
Keyword(s):  
Student Outcomes ◽  
Fixed Effects ◽  
Model Specification ◽  
Public Expenditures ◽  
Educational Goals ◽  
Instructional Expenditures ◽  
Education Production ◽  
Public Investments ◽  
Important Concern ◽  
The Impact

The relationship between public education expenditures and student outcomes remains an important concern for policy analysts, educational administrators, and the public at large. While previous studies have failed to identify a consistent relationship between public investments in education and positive student outcomes, most analyses have not accounted for the different educational goals associated with various instructional expenditure categories. This study builds on prior research by using Pennsylvania’s public school districts to test proposed improvements in model specification for the traditional education production function. Using longitudinal, fixed-effects models, a detailed disaggregation of instructional expenditures is undertaken in order to account for the likelihood that different instructional subcategories (i.e. regular programming, special education, and vocational instruction) influence student outcomes in varying ways. The results suggest that the impact of expenditures may be understated in previous studies based on a failure to account for these distinctions, particularly in the case of Mathematics education.

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