scholarly journals Modeling the consequences of the transition to parenthood: Applications of panel regression methods

2019 ◽  
Vol 36 (11-12) ◽  
pp. 4005-4026 ◽  
Author(s):  
Francisco Perales
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Regression Models ◽  
Transition To Parenthood ◽  
National Sample ◽  
Panel Regression ◽  
Cross Sectional ◽  
Time Dynamics ◽  
Advantages And Disadvantages ◽  
Panel Regression Models

The transition to parenthood is a topic of substantial interest to family researchers across the social sciences, and many theoretical paradigms have been invoked to understand how it affects men’s and women’s lives. While early empirical scholarship on the transition to parenthood relied on cross-sectional data and methods, the increasing availability of panel data has opened up new analytical pathways—including the possibility to track the same individuals over time as they approach and experience parenthood and their children grow older. By making full use of longitudinal data, researchers can both improve estimation of the consequences of parenthood, as well as advance knowledge by testing more nuanced and complex theoretical premises involving time dynamics. In this article, I present an overview of panel regression models, a family of specifications that can be leveraged for these purposes. In doing so, I discuss the data requirements, advantages and disadvantages of different models, pointing to useful examples of published research. The approaches considered include random effects and fixed effects panel regression models, specifications to model linear and nonlinear time dynamics, and specifications to handle dyadic data structures. The use of these techniques is exemplified via an application considering the effect of motherhood on time pressure using long-running panel data from an Australian national sample, the Household, Income and Labour Dynamics in Australia Survey ( n = 68,911 observations; 10,734 women).

Nurse Practitioner Scope of Practice Regulations and Nurse Practitioner Supply

2019 ◽  
pp. 107755871988842 ◽  
Author(s):  
Ryan Kandrack ◽  
Hilary Barnes ◽  
Grant R. Martsolf
Keyword(s):  
Health Professional ◽  
Access To Care ◽  
Nurse Practitioners ◽  
Nurse Practitioner ◽  
Fixed Effects ◽  
Regression Models ◽  
Scope Of Practice ◽  
Panel Regression ◽  
Cross Sectional ◽  
Panel Regression Models

Adopting full scope of practice (SOP) for nurse practitioners (NPs) is associated with improved access to care. One possible mechanism for these improvements is increased NP supply. Using county-level data, we fit cross-sectional and panel regression models to estimate the association between adopting full NP SOP and NP supply in general, and in rural and health professional shortage area—designated counties in particular. In cross-sectional analyses, we estimated positive associations between NP SOP and NP supply, though these relationships were only statistically significant when analyzing health professional shortage areas. In the panel regression models with county fixed effects, the estimated effects were attenuated toward zero and sometimes switched signs. Our findings suggest that improvements in access to care following adoption of full SOP may not be driven by increased NP supply but rather by increased capacity of NPs and physicians to provide care.

scholarly journals Changes in Family Income around the Time of Birth of Children in Germany between 1985 and 2004

2010 ◽  
Vol 35 (1) ◽  
Author(s):  
Alexander Schulze
Keyword(s):  
Family Support ◽  
Household Income ◽  
Fixed Effects ◽  
Regression Models ◽  
Family Income ◽  
Panel Regression ◽  
Short Term ◽  
Fixed Effects Panel Regression ◽  
Socioeconomic Consequences ◽  
Panel Regression Models

While the course and the determinants of fertility behaviour have been investigated intensively, the monetary consequences of birth have hardly been considered empirically to date. Therefore, this paper focuses on the short-term (equivalent) household income changes around the time of births in a longitudinal perspective and examines them for their causes. For the analyses of the longitudinal data (GSOEP-Data 1984-2005), fixed effects panel regression models were computed. The results show that the short-term socioeconomic consequences of birth have clearly increased in the last two decades and first births in particular are associated with disproportionately severe socioeconomic consequences, while further births are rarely accompanied by negative changes in the households’ socioeconomic situations. Furthermore, household income losses attributable to births only arise in double income households and increase gradually in line with a rising level of household income before birth. Hence, the analyses suggest the need for more adequate state assistance with respect to family support. Beside the provision of adequate infrastructural conditions which allow mothers to be employed, also the payments to compensate for child-related costs (“Kindergeld”) should be – in contrast to the present practice in Germany – increased and re-adjusted with respect to the child’s position in the birth sequence.

scholarly journals DYNAMIC LINEAR PANEL REGRESSION MODELS WITH INTERACTIVE FIXED EFFECTS

2015 ◽  
Vol 33 (1) ◽  
pp. 158-195 ◽  
Author(s):  
Hyungsik Roger Moon ◽  
Martin Weidner
Keyword(s):  
Fixed Effects ◽  
Regression Models ◽  
Panel Regression ◽  
Test Statistics ◽  
Finite Sample ◽  
Lm Test ◽  
Interactive Fixed Effects ◽  
Cross Sectional Dimension ◽  
Ls Estimator ◽  
Panel Regression Models

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, for example lagged-dependent variables. The first-order asymptotic theory of the least squares (LS) estimator of the regression coefficients is worked out in the limit where both the cross-sectional dimension and the number of time periods become large. We find two sources of asymptotic bias of the LS estimator: bias due to correlation or heteroscedasticity of the idiosyncratic error term, and bias due to predetermined (as opposed to strictly exogenous) regressors. We provide a bias-corrected LS estimator. We also present bias-corrected versions of the three classical test statistics (Wald, LR, and LM test) and show their asymptotic distribution is a χ2-distribution. Monte Carlo simulations show the bias correction of the LS estimator and of the test statistics also work well for finite sample sizes.

Fitting exponential regression models with two-way fixed effects

2020 ◽  
Vol 20 (2) ◽  
pp. 468-480
Author(s):  
Koen Jochmans ◽  
Vincenzo Verardi
Keyword(s):  
Panel Data ◽  
Cross Section ◽  
Fixed Effects ◽  
Regression Models ◽  
Bilateral Trade ◽  
Dyadic Interactions ◽  
Cross Sectional ◽  
Trade Data ◽  
Exponential Regression ◽  
Special Case

In this article, we introduce the commands twexp and twgravity, which implement the estimators developed in Jochmans (2017, Review of Economics and Statistics 99: 478–485) for exponential regression models with two-way fixed effects. twexp is applicable to generic n × m panel data. twgravity is written for the special case where the dataset is a cross-section on dyadic interactions between n agents. A prime example is cross-sectional bilateral trade data, where the model of interest is a gravity equation with importer and exporter effects. Both twexp and twgravity can deal with data where n and m are large, that is, where there are many fixed effects. These commands use Mata and are fast to execute.

scholarly journals Effect of inventory management on profitability: evidence from the Polish food industry: Case study

2020 ◽  
Vol 66 (No. 5) ◽  
pp. 234-242
Author(s):  
Zbigniew Gołaś
Keyword(s):  
Panel Data ◽  
Financial Performance ◽  
Inventory Management ◽  
Regression Models ◽  
Food Industry ◽  
Panel Regression ◽  
Management Efficiency ◽  
Causative Link ◽  
Panel Regression Models

The main purpose of this study is to verify the causative link between inventory performance and profitability of food companies. This was done using the panel data methodology at the level of Polish food industry sub-sectors. The study takes account of the inventory mix, which includes the stocks of raw and other materials, work-in-progress, finished products and commodities. As shown by the analysis, the 2005–2017 period witnessed a decline in the share of inventories in total assets and in current assets. That trend was accompanied by an improvement in inventory management efficiency. The study also found that the days sales of inventory for total stocks clearly tends to become shorter due to a reduction in the days in inventory ratio for materials and finished products. Based on panel regression models, this study demonstrated that an improvement in inventory management efficiency is positively correlated with financial performance, measured as the return on operating assets.

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