scholarly journals Recentered influence functions (RIFs) in Stata: RIF regression and RIF decomposition

2020 ◽  
Vol 20 (1) ◽  
pp. 51-94 ◽  
Author(s):  
Fernando Rios-Avila
Keyword(s):  
Fixed Effects ◽  
Decomposition Analysis ◽  
High Dimensional ◽  
Large Set ◽  
Influence Functions ◽  
Analysis Framework ◽  
Quantile Regressions ◽  
Rif Regression ◽  
Linear Regressions ◽  
Partial Effects

Recentered influence functions (RIFs) are statistical tools popularized by Firpo, Fortin, and Lemieux (2009 , Econometrica 77: 953–973) for analyzing unconditional partial effects on quantiles in a regression analysis framework (unconditional quantile regressions). The flexibility and simplicity of these tools have opened the possibility to extend the analysis to other distributional statistics using linear regressions or decomposition approaches. In this article, I introduce one function and two commands to facilitate the use of RIFs in the analysis of outcome distributions: rifvar() is an egen extension used to create RIFs for a large set of distributional statistics, rifhdreg facilitates the estimation of RIF regressions enabling the use of high-dimensional fixed effects, and oaxaca_rif implements Oaxaca–Blinder decomposition analysis (RIF decompositions).

scholarly journals Dynamic Effects of Co-Ethnic Networks on Immigrants’ Economic Success*

2021 ◽  
Author(s):  
Michele Battisti ◽  
Giovanni Peri ◽  
Agnese Romiti
Keyword(s):  
Fixed Effects ◽  
Large Set ◽  
Capital Investments ◽  
Economic Success ◽  
Skilled Immigrants ◽  
Ethnic Networks ◽  
Initial Location ◽  
Ethnic Germans ◽  
Human Capital Investments ◽  
Catch Up

Abstract This paper investigates how co-ethnic networks affect the economic success of immigrants. Using longitudinal data of immigrants in Germany and including a large set of fixed effects and pre-migration controls to address the possible endogeneity of initial location, we find that immigrants in districts with larger co-ethnic networks are more likely to be employed soon after arrival. This advantage fades after four years, as migrants located in places with smaller co-ethnic networks catch up due to greater human capital investments. These effects appear stronger for lower-skilled immigrants, as well as for refugees and Ethnic Germans.

Currency Unions and Trade: A PPML Re‐assessment with High‐dimensional Fixed Effects

2018 ◽  
Vol 81 (3) ◽  
pp. 487-510 ◽  
Author(s):  
Mario Larch ◽  
Joschka Wanner ◽  
Yoto V. Yotov ◽  
Thomas Zylkin
Keyword(s):  
Fixed Effects ◽  
High Dimensional ◽  
Currency Unions

Gender wage gap decomposition methods: Comparative analysis

2021 ◽  
Vol 62 ◽  
pp. 5-31
Author(s):  
Sergey Roshchin ◽  
◽  
Natalya Yemelina ◽  
Keyword(s):  
Comparative Analysis ◽  
Gender Wage Gap ◽  
Wage Gap ◽  
Decomposition Methods ◽  
Influence Functions ◽  
Quantile Regressions ◽  
Men And Women ◽  
Distribution Parameters ◽  
Monitoring Survey ◽  
The Mean

This study introduces a comparative analysis of the gender wage gap decomposition methods with the Russian Longitudinal Monitoring Survey (RLMS) data for 2018. To decompose the differences in average wages, approaches based on the Oaxaca–Blinder decomposition are used. Apart from the mean wages, the study focuses on other distribution statistics. Using the quantile regressions, the wage gap between men and women is decomposed for the distribution parameters such as median, lower and upper deciles. The decomposition estimates of conditional and unconditional (based on recentered influence functions) quantile regressions are compared.

The flexibility of corporate payouts vis-à-vis capital investment: some UK evidence

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ioannis Chasiotis ◽  
Andreas G. Georgantopoulos
Keyword(s):  
Fixed Effects ◽  
Firm Behavior ◽  
Estimation Methods ◽  
Share Repurchases ◽  
Quantile Regressions ◽  
Growth Opportunities ◽  
Content Type ◽  
Conditional Mean ◽  
Heterogeneous Firm ◽  
The Uk

PurposeThis study investigates the relative flexibility of payouts vis-à-vis investment in the UK, motivated by concerns regarding this market's distinct payout characteristics and limited relevant research. It addresses the information gap related to the use of conditional mean estimations and examines firm behavior across the investment distribution.Design/methodology/approachThe sample is an unbalanced panel of 6,173 firm-year observations, from 271 non-financial firms in the FTSE-All Share Index, during 1990–2019. Estimation methods include pooled- ordinary least squares (OLS) and firm fixed-effects regressions as well as unconditional quantile regressions with firm fixed effects.FindingsFor the “average” firm results show a negative relationship between share repurchases and investment, amplified in the presence of financial constraints and growth opportunities. Quantile regressions analysis reveals heterogeneous firm behavior as this relationship becomes stronger in successive quantiles of the investment distribution and disappears at the upper/lower extremes. Results suggest that UK firms exploit the inherent flexibility of share repurchases to facilitate investment. However, this flexibility appears irrelevant to firms with extremely high/low investment, characterized by significant differences in growth opportunities, cash flows and external financing cost. Dividends and investment are independent across the investment distribution, underlining the rigidity of dividends in the UK.Originality/valueTo the best of our knowledge, this is the first study to investigate the relative flexibility of payouts vis-à-vis investment in the UK, using firm-level financial data and at points other than the conditional mean. Its value lies in that it shows that share repurchases facilitate rather than impede investment and thus do not corroborate relevant concerns by economists and policymakers. Additionally, by utilizing a relatively new methodology it uncovered heterogeneous firm behavior across the investment distribution suggesting that conditional mean estimations should be applied with caution at least for highly heterogeneous samples.

WHAT DO QUANTILE REGRESSIONS IDENTIFY FOR GENERAL STRUCTURAL FUNCTIONS?

2014 ◽  
Vol 31 (5) ◽  
pp. 1102-1116 ◽  
Author(s):  
Yuya Sasaki
Keyword(s):  
Partial Derivative ◽  
General Class ◽  
Weighted Average ◽  
Causal Effects ◽  
Quantile Regressions ◽  
Conditional Quantile ◽  
Mild Conditions ◽  
Structural Functions ◽  
Partial Effects

This paper shows what quantile regressions identify for general structural functions. Under fairly mild conditions, the quantile partial derivative identifies a weighted average of heterogeneous structural partial effects among the subpopulation of individuals at the conditional quantile of interest. This result justifies the use of quantile regressions as means of measuring heterogeneous causal effects for a general class of structural functions with multiple unobservables.

scholarly journals Fast Poisson estimation with high-dimensional fixed effects

2020 ◽  
Vol 20 (1) ◽  
pp. 95-115 ◽  
Author(s):  
Sergio Correia ◽  
Paulo Guimarães ◽  
Tom Zylkin
Keyword(s):  
Least Squares ◽  
Fixed Effects ◽  
Maximum Likelihood Estimates ◽  
High Dimensional ◽  
Software Components ◽  
Iteratively Reweighted Least Squares ◽  
Convergence Properties ◽  
New Techniques ◽  
Boston College ◽  
Pseudo Maximum Likelihood

In this article, we present ppmlhdfe, a new command for estimation of (pseudo-)Poisson regression models with multiple high-dimensional fixed effects (HDFE). Estimation is implemented using a modified version of the iteratively reweighted least-squares algorithm that allows for fast estimation in the presence of HDFE. Because the code is built around the reghdfe package ( Correia, 2014 , Statistical Software Components S457874, Department of Economics, Boston College), it has similar syntax, supports many of the same functionalities, and benefits from reghdfe‘s fast convergence properties for computing high-dimensional leastsquares problems. Performance is further enhanced by some new techniques we introduce for accelerating HDFE iteratively reweighted least-squares estimation specifically. ppmlhdfe also implements a novel and more robust approach to check for the existence of (pseudo)maximum likelihood estimates.

scholarly journals Mastering Panel Metrics: Causal Impact of Democracy on Growth

2019 ◽  
Vol 109 ◽  
pp. 77-82 ◽  
Author(s):  
Shuowen Chen ◽  
Victor Chernozhukov ◽  
Iván Fernández-Val
Keyword(s):  
Panel Data ◽  
Statistical Inference ◽  
Fixed Effects ◽  
State Of The Art ◽  
Panel Data Analysis ◽  
High Dimensional ◽  
Econometric Methods ◽  
Long Run ◽  
Causal Impact ◽  
The Relationship

We revisit the panel data analysis of Acemoglu et al. (forthcoming) on the relationship between democracy and economic growth using state-of-the-art econometric methods. We argue that panel data settings are high-dimensional, resulting in estimators to be biased to a degree that invalidates statistical inference. We remove these biases by using simple analytical and sample-splitting methods, and thereby restore valid statistical inference. We find that debiased fixed effects and Arellano-Bond estimators produce higher estimates of the long-run effect of democracy on growth, providing even stronger support for the key hypothesis of Acemoglu et al.

scholarly journals Higher Sugar-Sweetened Beverage Retail Prices After Excise Taxes in Oakland and San Francisco

2020 ◽  
Vol 110 (7) ◽  
pp. 1017-1023 ◽  
Author(s):  
Jennifer Falbe ◽  
Matthew M. Lee ◽  
Scott Kaplan ◽  
Nadia A. Rojas ◽  
Alberto M. Ortega Hinojosa ◽  
...  
Keyword(s):  
San Francisco ◽  
Fixed Effects ◽  
Weighted Average ◽  
High Dimensional ◽  
Difference In Differences ◽  
Sugar Sweetened Beverage ◽  
Excise Taxes ◽  
Sweetened Beverage ◽  
Diet Soda ◽  
Retail Prices

Objectives. To examine how much sugar-sweetened beverage (SSB) excise taxes increased SSB retail prices in Oakland and San Francisco, California. Methods. We collected pretax (April–May 2017) and posttax (April–May 2018) retail prices of SSBs and non-SSBs from 155 stores in Oakland, San Francisco, and comparison cities. We analyzed data using difference-in-differences high-dimensional fixed-effects regressions, weighted by regional beverage sales. Results. Across all beverage sizes, the weighted average price of SSBs increased by 0.92 cents per ounce (95% confidence interval [CI] = 0.28, 1.56) in Oakland and 1.00 cents per ounce (95% CI = 0.35, 1.65) in San Francisco, compared with prices in untaxed cities. The tax did not significantly alter prices of water, 100% juice, or milk of any size examined. Diet soda only, among non-SSBs, exhibited a higher price increase for some sizes in taxed cities. Conclusions. Within 4 to 10 months of implementation, Oakland’s and San Francisco’s SSB excise taxes significantly increased SSB retail prices by approximately the amount of the taxes, a key mechanism for reducing consumption.

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