Of Fixed-Effects and Time-Invariant Variables

2011 ◽  
Vol 19 (2) ◽  
pp. 119-122 ◽  
Author(s):  
Nathaniel Beck
Keyword(s):  
Panel Data ◽  
Data Model ◽  
Fixed Effects ◽  
Fixed Effect ◽  
Panel Data Model ◽  
Vector Decomposition ◽  
Time Invariant

What follows is a longish controversy (two critiques, a reply and two rejoinders) over the quality of the estimates and associated SEs provided by Plümper and Troeger's (2007) “fixed-effect vector decomposition” (FEVD) procedure; Plümper and Troeger (PT) will refer to that article and not any persons. My role is to lay out some issues that separate the authors rather than to adjudicate between them. As with many controversies, a bit of heat is generated along with some light. Readers care a bit less than the authors about what was said when, but they do care a lot about what appropriate method to use when a panel data model has both unit-specific intercepts and variables that are invariant over a unit. Thus, I also take it upon myself to discuss some things that I gleaned from this controversy; this discussion has a bit less heat than what follows, but of course readers should judge the evidence for themselves.

scholarly journals Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data Model

2018 ◽  
Vol 11 (3) ◽  
pp. 44 ◽  
Author(s):  
Karen Yan ◽  
Qi Li
Keyword(s):  
Panel Data ◽  
Data Model ◽  
Numerical Optimization ◽  
Fixed Effects ◽  
Quantile Function ◽  
Panel Data Model ◽  
Nonparametric Method ◽  
Conditional Quantile ◽  
Finite Samples ◽  
Conditional Quantile Function

This paper develops a nonparametric method to estimate a conditional quantile function for a panel data model with an additive individual fixed effects. The proposed method is easy to implement, it does not require numerical optimization and automatically ensures quantile monotonicity by construction. Monte Carlo simulations show that the proposed estimator performs well in finite samples.

scholarly journals Maternal Mortality in Ghana: Impact of the Fee-Free Delivery Policy and the National Health Insurance Scheme

2015 ◽  
Vol 4 (3) ◽  
pp. 232
Author(s):  
Seidu Sofo ◽  
Emmanuel Thompson
Keyword(s):  
Health Insurance ◽  
Panel Data ◽  
Maternal Mortality ◽  
National Health Insurance ◽  
National Health ◽  
Data Model ◽  
Fixed Effects ◽  
Panel Data Model ◽  
Skilled Delivery ◽  
The Impact

<p>Maternal mortality (MMR) is the second largest cause of female deaths in Ghana. Yet, many households cannot afford the cost of skilled delivery The study utilized the Panel Data Model to examine the impact of the fee-free delivery (FDP) and the National Health Insurance Policy (NIP) exemptions on MMR in Ghana. The Demographic and Health Survey reports on Ghana from 2002 to 2009 served as the main data source. Data were analyzed using Panel data model with within group fixed effects estimator. MMR declined significantly over the period studied. Both FDP and NIP positively impacted MMR at a 5% level of significance. In addition, skilled delivery was a significant predictor of MMR. Stakeholders would do well to ensure NIP is adequately funded in order to sustain the decline in MMR.</p><p> </p><p><strong><br /></strong></p>

scholarly journals Optimal trade-off between sample size, precision of supervision, and selection probabilities for the unbalanced fixed effects panel data model

2020 ◽  
Vol 24 (21) ◽  
pp. 15937-15949
Author(s):  
Giorgio Gnecco ◽  
Federico Nutarelli ◽  
Daniela Selvi
Keyword(s):  
Panel Data ◽  
Sample Size ◽  
Upper Bound ◽  
Data Model ◽  
Fixed Effects ◽  
Conditional Variance ◽  
Panel Data Model ◽  
Generalization Error ◽  
Trade Off ◽  
Selection Probabilities

Abstract This paper is focused on the unbalanced fixed effects panel data model. This is a linear regression model able to represent unobserved heterogeneity in the data, by allowing each two distinct observational units to have possibly different numbers of associated observations. We specifically address the case in which the model includes the additional possibility of controlling the conditional variance of the output given the input and the selection probabilities of the different units per unit time. This is achieved by varying the cost associated with the supervision of each training example. Assuming an upper bound on the expected total supervision cost and fixing the expected number of observed units for each instant, we analyze and optimize the trade-off between sample size, precision of supervision (the reciprocal of the conditional variance of the output) and selection probabilities. This is obtained by formulating and solving a suitable optimization problem. The formulation of such a problem is based on a large-sample upper bound on the generalization error associated with the estimates of the parameters of the unbalanced fixed effects panel data model, conditioned on the training input dataset. We prove that, under appropriate assumptions, in some cases “many but bad” examples provide a smaller large-sample upper bound on the conditional generalization error than “few but good” ones, whereas in other cases the opposite occurs. We conclude discussing possible applications of the presented results, and extensions of the proposed optimization framework to other panel data models.

Forced Displacement in Colombia: What Determines Expulsion and Reception in Municipalities?

2014 ◽  
Vol 20 (4) ◽  
pp. 585-597 ◽  
Author(s):  
Ximena Dueñas ◽  
Paola Palacios ◽  
Blanca Zuluaga
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Independent Variables ◽  
Panel Data Estimation ◽  
Vector Decomposition ◽  
Displaced People ◽  
Time Invariant ◽  
Data Estimation ◽  
Conflict Intensity ◽  
Municipal Level

AbstractThis document explores the expulsion and reception determinants of displaced people among Colombian municipalities. For this purpose, we use fixed effects panel data estimations for the period 2004–2009, with municipality year as the unit of analysis. To the best of our knowledge, this is the first paper in Colombia that focuses on reception and the first one using panel data at municipal level to explain expulsion and reception. We find that, contrary to what one may expect, some independent variables affect both expulsion and reception of displaced people in the same direction; for instance, municipalities where homicide rates and conflict intensity are high, are associated with both higher reception and expulsion rates. In addition to the conventional panel data estimation, we also run a fixed effect vector decomposition to identify the explicit effects of certain time-invariant variables.

scholarly journals The Effect of ASEAN-China Free Trade Area (ACFTA) on Indonesia Export

ETIKONOMI ◽  
2016 ◽  
Vol 15 (2) ◽  
pp. 125-138
Author(s):  
Indriyani Indriyani
Keyword(s):  
Panel Data ◽  
Free Trade ◽  
Cross Section ◽  
Data Model ◽  
Free Trade Area ◽  
Fixed Effect ◽  
Panel Data Model ◽  
Phnom Penh ◽  
Trade Area ◽  
Asean Countries

ASEAN-China Free Trade Area (ACFTA) is an agreement between the members of ASEAN and China to create a free trade area by removing tariff and non-tariff barriers. This agreement begins with the signing of the agreement on November 5, 2002 in Phnom Penh. Implementation is done in phases beginning January 1, 2004. The purpose of this study determines the effect of the implementation of ACFTA on Indonesia's exports to the ASEAN countries and China. This study complements previous research regarding the ACFTA. The data used in this study are the data of Indonesian exports to ASEAN countries and China for 15 years from 2000 until 2014. The tests were conducted with a fixed effect panel data model with cross section SUR. The results of this study indicate that the ACFTA increase Indonesian exports to the ASEAN countries and China.DOI: 10.15408/etk.v15i2.3331

scholarly journals Kebijakan Anti Dumping dan Trade Deflection: Studi Kasus Synthetic Staple Fibre Polyester (PSF)

2009 ◽  
Vol 10 (1) ◽  
pp. 35-52
Author(s):  
Wara Agustina Rukminf ◽  
Ferry Irawan
Keyword(s):  
European Union ◽  
Panel Data ◽  
Early Warning ◽  
Data Model ◽  
Fixed Effects ◽  
Staple Fibre ◽  
Panel Data Model ◽  
Negative Effect

Abstract. This research empirically examines whether a country's anti dumping policy can distort export of another country to third markets. This research tries to explore about trade deflection of Indonesia's export on Synthetic Staple Fibre Polyester (PSF) HS 550320 to non-European Union as the result of European Union's (EU) anti dumping policy on Indonesia. This research uses panel data model (fixed effects) and 20 countries (non-European Union) of Indonesia's PSF export during ten years (1996-2005). We find evidence that trade deflection for Indonesia's export on Synthetic Staple Fibre Polyester (PSF) HS 550320 occurred. Because of European Union had imposed anti dumping duty on Indonesia, Indonesia's export to nonEuropean Union had increased ranged from 25 percent to 44 percent. This result shows that dumping duty from European Union does not fully carry out negative effect for Indonesia, furthermore thisphenomena can be used as ”early warning” for Indonesia both for case of Indonesia as exporting country or third countries.

Sign in / Sign up

Export Citation Format

Share Document