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.

scholarly journals Corruption and Its Effects on Sustainable Economic Performance

2019 ◽  
Vol 6 (2) ◽  
pp. 12
Author(s):  
Michael Appiah ◽  
Derrick Yaw Idan Frowne ◽  
Anita Idan Frowne
Keyword(s):  
Model Selection ◽  
Human Development ◽  
Economic Performance ◽  
Fixed Effects ◽  
Theoretical Perspective ◽  
Fixed Effects Model ◽  
Data Set ◽  
Hausman Test ◽  
Explanatory Variables ◽  
Independent Variables

<p>The study examines corruption and its effects on achieving sustainable economic performance in Africa with a data set from 2002-2017. The Hausman Test for determining the appropriate model selection between Random and Fixed effects was employed with the fixed effects model of estimation chosen to be the appropriate method of estimation indicating that the degree of relationship and significant between corruption and sustainable economic performance in negative. The R² explains that 95% of variations in sustainable economic performance in the estimation of prime independent variables. Aside corruption having a negative and insignificant impact on sustainable economic performance, an increase in human development and labour resulted in a positive and significant relations on sustainable economic performance, with the rest of the explanatory variables having a poor and negative affiliation with sustainable economic performance. The above therefore follows the empirical, conventional and theoretical perspective that corruption declines growth and sustainability both domestically and globally.</p>

scholarly journals Trade and Income—Exploiting Time Series in Geography

2019 ◽  
Vol 11 (4) ◽  
pp. 1-35 ◽  
Author(s):  
James Feyrer
Keyword(s):  
Time Series ◽  
Fixed Effects ◽  
Time Varying ◽  
Omitted Variables ◽  
Trade Growth ◽  
Cross Country ◽  
Time Invariant ◽  
Variable Problem ◽  
Positive Effect ◽  
Over Time

Establishing a robust causal relationship between trade and income has been difficult. Frankel and Romer (1999) uses a geographic instrument to identify a positive effect of trade on income. Rodriguez and Rodrik (2001) shows that these results are not robust to controlling for omitted variables such as distance to the equator or institutions. This paper solves the omitted variable problem by generating a time-varying geographic instrument. Improvements in aircraft technology have caused the quantity of world trade carried by air to increase over time. Country pairs with relatively short air routes compared to sea routes benefit more from this change in technology. This heterogeneity can be used to generate a geography-based instrument for trade that varies over time. The time-series variation allows for controls for country fixed effects, eliminating the bias from time-invariant variables such as distance from the equator or historically determined institutions. Trade has a significant effect on income with an elasticity of roughly one-half. Differences in predicted trade growth can explain roughly 17 percent of the variation in cross-country income growth between 1960 and 1995. (JEL F14, F43, L93)

Abstract MP37: Macroeconomic Growth is Associated with Increases in Cardiovascular Mortality in Countries with Lower Social Protection Spending

Circulation ◽  
2015 ◽  
Vol 131 (suppl_1) ◽  
Author(s):  
Usama Bilal ◽  
Manuel Franco ◽  
Thomas A Glass
Keyword(s):  
Economic Growth ◽  
Cardiovascular Mortality ◽  
Fixed Effects ◽  
Social Protection ◽  
Welfare States ◽  
Time Varying ◽  
Fixed Effects Model ◽  
Data Set ◽  
Macroeconomic Growth ◽  
Cvd Mortality

Background: Macroeconomic growth has been shown to be associated with increases in cardiovascular (CVD) mortality. However, it is unclear whether concurrent social protection policies may mitigate the observed associations. Objective: To study if social protection expenditure modifies the association between macroeconomic growth and cardiovascular mortality. Methods: We included 21 OECD countries from 1980 to 2010 with available data in the Comparative Welfare States Data Set and the WHO Mortality Database. Gross Domestic Product (GDP) was used as a proxy for economic growth. Age-adjusted cardiovascular mortality rates were calculated. Countries were divided into tertiles of average Social Protection expenditure. We used fixed-effect models to study the association of GDP growth with CVD mortality stratified by tertile of social protection expenditure. We included four lagged GDP terms to account for the cyclical nature of GDP. A second fixed-effects model was fitted with time-varying linear and quadratic social protection expenditure and its interaction with GDP. Results: Overall, a 1% increase in GDP was associated with an increase in CVD mortality of 0.5% (95% CI: 0.21-0.83%, p=0.001). In countries with high and medium social protection expenditure, GDP increases were not associated with changes in CVD mortality (p=0.80 and p=0.52 respectively). In countries with the lowest social protection expenditure, a 1% GDP increase was associated with a significant increase in CVD mortality of 0.7% (95% CI: 0.04-1.32% p=0.03). These results were consistent in analysis using time-varying social protection expenditure (Figure). Conclusion: Our results highlight the need for social protection policies to accompany economic growth to mitigate its potential deleterious effects on cardiovascular diseases. Further research should study specific policies that mitigate the harmful effects of macroeconomic growth.

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 On the Fixed-Effects Vector Decomposition

2011 ◽  
Vol 19 (2) ◽  
pp. 123-134 ◽  
Author(s):  
Trevor Breusch ◽  
Michael B. Ward ◽  
Hoa Thi Minh Nguyen ◽  
Tom Kompas
Keyword(s):  
Monte Carlo ◽  
Instrumental Variables ◽  
Fixed Effects ◽  
Formal Analysis ◽  
Standard Errors ◽  
Panel Data Models ◽  
Time Varying ◽  
Vector Decomposition ◽  
Time Invariant ◽  
Instrumental Variables Approach

This paper analyzes the properties of the fixed-effects vector decomposition estimator, an emerging and popular technique for estimating time-invariant variables in panel data models with group effects. This estimator was initially motivated on heuristic grounds, and advocated on the strength of favorable Monte Carlo results, but with no formal analysis. We show that the three-stage procedure of this decomposition is equivalent to a standard instrumental variables approach, for a specific set of instruments. The instrumental variables representation facilitates the present formal analysis that finds: (1) The estimator reproduces exactly classical fixed-effects estimates for time-varying variables. (2) The standard errors recommended for this estimator are too small for both time-varying and time-invariant variables. (3) The estimator is inconsistent when the time-invariant variables are endogenous. (4) The reported sampling properties in the original Monte Carlo evidence do not account for presence of a group effect. (5) The decomposition estimator has higher risk than existing shrinkage approaches, unless the endogeneity problem is known to be small or no relevant instruments exist.

scholarly journals EFFECTS OF SELECTED COMPANY-SPECIFIC VARIABLES IN THE DETERMINATION OF COMPANY LEVERAGE: EVIDENCE FROM TEXTILE INDUSTRY OF BANGLADESH

2021 ◽  
pp. 19-29
Keyword(s):  
Textile Industry ◽  
Fixed Effects ◽  
Negative Impact ◽  
Positive Impact ◽  
Stock Exchange ◽  
Fixed Effects Model ◽  
Data Set ◽  
Hausman Test ◽  
Asset Turnover

The purpose of this study is to investigate the effects of profitability, liquidity, size, tangibility, and asset turnover on the leverage of the textile industry of Bangladesh. This paper analyzed 20 companies out of 56 companies listed in the Dhaka Stock Exchange. The data set is for the periods from 2016 to 2019. To find the effects on the dependent variable, the Fixed Effects Model has been used which has been selected using the Hausman test. To test heteroskedasticity, the Breusch-Pagan heteroskedasticity test has been used. The study found size, profitability, and tangibility having a significant effect. While size and tangibility have a positive impact on leverage, profitability has a negative impact. The findings are diversified in nature. The results are not all consistent with the previous studies conducted in different developing countries. So, the policymakers should have in-depth insights while making decisions.

Efficient Estimation of Time-Invariant and Rarely Changing Variables in Finite Sample Panel Analyses with Unit Fixed Effects

2007 ◽  
Vol 15 (2) ◽  
pp. 124-139 ◽  
Author(s):  
Thomas Plümper ◽  
Vera E. Troeger
Keyword(s):  
Fixed Effects ◽  
Error Term ◽  
Efficient Estimation ◽  
Fixed Effects Model ◽  
Finite Sample ◽  
Real World Data ◽  
Third Stage ◽  
Finite Sample Properties ◽  
Time Invariant ◽  
Estimation Of Time

This paper suggests a three-stage procedure for the estimation of time-invariant and rarely changing variables in panel data models with unit effects. The first stage of the proposed estimator runs a fixed-effects model to obtain the unit effects, the second stage breaks down the unit effects into a part explained by the time-invariant and/or rarely changing variables and an error term, and the third stage reestimates the first stage by pooled OLS (with or without autocorrelation correction and with or without panel-corrected SEs) including the time-invariant variables plus the error term of stage 2, which then accounts for the unexplained part of the unit effects. We use Monte Carlo simulations to compare the finite sample properties of our estimator to the finite sample properties of competing estimators. In doing so, we demonstrate that our proposed technique provides the most reliable estimates under a wide variety of specifications common to real world data.

scholarly journals Impact of Capital Structure on Financial Performance: A Study of Select Automobile Companies in India

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Rahul Sarkar ◽  
Ram Prahlad Choudhary
Keyword(s):  
Capital Structure ◽  
Financial Performance ◽  
Fixed Effects ◽  
Wald Test ◽  
Panel Regression ◽  
Fixed Effects Model ◽  
Short Term ◽  
Hausman Test ◽  
Return On Equity ◽  
Random Effects Models

There exists a debate as to whether capital structure variables and financial performance are associated or not. This study aims to understand the movement of shareholders return in the context of capital structure composition. With fifteen years data and sixteen automobile companies, both pooled regression and panel regression (Fixed effects and Random effects models) have been used and the best fitted model have been selected through Hausman test and Wald Test. The best fitted model was found to be the Fixed Effects model and according to that equity and short-term debt affects return on equity (ROE) positively and negatively respectively and both are highly statistically significant. The model explained almost 57% variation in ROE with no autocorrelation problem in error term. The study is of high significance to the investors as well as firms for decision making as the study reveals ROE is fairly explained by Capital Structure composition.

Fixed-Effects Vector Decomposition: Properties, Reliability, and Instruments

2011 ◽  
Vol 19 (2) ◽  
pp. 147-164 ◽  
Author(s):  
Thomas Plümper ◽  
Vera E. Troeger
Keyword(s):  
Fixed Effects ◽  
Shrinkage Estimator ◽  
Time Varying ◽  
Finite Sample ◽  
Simultaneous Presence ◽  
Political Analysis ◽  
Vector Decomposition ◽  
Finite Sample Properties ◽  
Time Invariant ◽  
Decomposition Properties

This article reinforces our 2007 Political Analysis publication in demonstrating that the fixed-effects vector decomposition (FEVD) procedure outperforms any other estimator in estimating models that suffer from the simultaneous presence of time-varying variables correlated with unobserved unit effects and time-invariant variables. We compare the finite-sample properties of FEVD not only to the Hausman-Taylor estimator but also to the pretest estimator and the shrinkage estimator suggested by Breusch, Ward, Nguyen and Kompas (BWNK), and Greene in this symposium. Moreover, we correct the discussion of Greene and BWNK of FEVD's asymptotic and finite-sample properties.

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