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Arjun S Wilkins

Datos Biográficos

ID4123333
NOMBREArjun S Wilkins
NOMBRESArjun S
APELLIDOWilkins
FIRMAWILKINS A S
VERIFICADONo
TOTAL DE OBRAS3
TOTAL DE CITAS89
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2011
AÑO MÁS RECIENTE DE PUBLICACIÓN2018
ÍNDICE H3
  • To Lag or Not to Lag

    Open Access•Arjun S Wilkins, Arjun Wilkins•ARTICLE•Political Science Research and…•2018•Citada por: 75•Referencias: 26

    Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process. I demonstrate that these concerns are easily resolved by specifying a regression model that accounts for autocorrelation in the error term. This ac…

  • Electoral Security of Members of the U.S. House, 1900–2006

    Open Access•Arjun S Wilkins, Arjun Wilkins•ARTICLE•Legislative Studies Quarterly•2012•Citada por: 3•Referencias: 28

    Previous studies have documented that the increase in the incumbency advantage in the 1960s did not decrease the probability of defeat of incumbents in the U.S. House. I define a method for establishing bounds on the probability of incumbent defeat and find that it decreases significantly in the 1950s, before the rise of the incumbency advantage. Incumbency advantage does not have a direct relationship with incumbent defeat rates, raising questio…

  • The 2010 Elections

    Open Access•D Brady, David W Brady et al.•ARTICLE•PS Political Science & Politics•2011•Citada por: 11•Referencias: 6

    In President Obama's words, the Democratic Party experienced a “shellacking” in the 2010 elections. In particular, the net loss of 63 House seats was the biggest midterm loss suffered by a party since 1938—the largest in the lifetimes of approximately 93% of the American population

  • To Lag or Not to Lag

    Open Access•Arjun S Wilkins, Arjun Wilkins•ARTICLE•Political Science Research and…•2018•Citada por: 75•Referencias: 26

    Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process. I demonstrate that these concerns are easily resolved by specifying a regression model that accounts for autocorrelation in the error term. This ac…

  • The 2010 Elections

    Open Access•D Brady, David W Brady et al.•ARTICLE•PS Political Science & Politics•2011•Citada por: 11•Referencias: 6

    In President Obama's words, the Democratic Party experienced a “shellacking” in the 2010 elections. In particular, the net loss of 63 House seats was the biggest midterm loss suffered by a party since 1938—the largest in the lifetimes of approximately 93% of the American population

  • Electoral Security of Members of the U.S. House, 1900–2006

    Open Access•Arjun S Wilkins, Arjun Wilkins•ARTICLE•Legislative Studies Quarterly•2012•Citada por: 3•Referencias: 28

    Previous studies have documented that the increase in the incumbency advantage in the 1960s did not decrease the probability of defeat of incumbents in the U.S. House. I define a method for establishing bounds on the probability of incumbent defeat and find that it decreases significantly in the 1950s, before the rise of the incumbency advantage. Incumbency advantage does not have a direct relationship with incumbent defeat rates, raising questio…

  • The 2010 Elections

    Open Access•D Brady, David W Brady et al.•ARTICLE•PS Political Science & Politics•2011•Citada por: 11•Referencias: 6

    In President Obama's words, the Democratic Party experienced a “shellacking” in the 2010 elections. In particular, the net loss of 63 House seats was the biggest midterm loss suffered by a party since 1938—the largest in the lifetimes of approximately 93% of the American population

  • Electoral Security of Members of the U.S. House, 1900–2006

    Open Access•Arjun S Wilkins, Arjun Wilkins•ARTICLE•Legislative Studies Quarterly•2012•Citada por: 3•Referencias: 28

    Previous studies have documented that the increase in the incumbency advantage in the 1960s did not decrease the probability of defeat of incumbents in the U.S. House. I define a method for establishing bounds on the probability of incumbent defeat and find that it decreases significantly in the 1950s, before the rise of the incumbency advantage. Incumbency advantage does not have a direct relationship with incumbent defeat rates, raising questio…

  • To Lag or Not to Lag

    Open Access•Arjun S Wilkins, Arjun Wilkins•ARTICLE•Political Science Research and…•2018•Citada por: 75•Referencias: 26

    Lagged dependent variables (LDVs) have been used in regression analysis to provide robust estimates of the effects of independent variables, but some research argues that using LDVs in regressions produces negatively biased coefficient estimates, even if the LDV is part of the data-generating process. I demonstrate that these concerns are easily resolved by specifying a regression model that accounts for autocorrelation in the error term. This ac…

Economics (2 obras) · Electoral Systems and Political Participation (2 obras) · Mathematics (2 obras) · Political economy (2 obras) · Political science (2 obras) · Autocorrelation (1 obras) · Computer Science (1 obras) · Democracy (1 obras) · Demography (1 obras) · Econometrics (1 obras)

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