Modeling Dynamics in Time-SeriesCross-Section Political Economy Data

Ethylene-acrylic acid type interpolymer compositions and films having increased slip and reduced block. A compositionally uniform interpolymer is compounded with at least one amide additive of the formula R1-CO-NH-R2 in which R1 is selected from saturated alkyl groups having from 13 to 25 carbon atoms and mono-olefinically unsaturated alkyl groups having from 17 to 23 carbon atoms and in which R2 is selected from saturated alkyl groups having 14 to 26 carbon atoms and mono-olefinically unsaturated alkyl groups having from 18 to 24 carbon atoms; and optionally, finely divided inorganic. In another embodiment, a compositionally uniform or a compositionally non-uniform interpolymer is compounded with: (i) about 0.025-1 weight percent of saturated secondary fatty acid amide; (ii) about 0.025-1 weight percent of unsaturated or mixed unsaturated secondary fatty acid amide; and optionally (iii) about 0.025-1.5 weight percent of finely divided inorganic.

[1]  James Davidson,et al.  Econometric Modelling of the Aggregate Time-Series Relationship Between Consumers' Expenditure and Income in the United Kingdom , 1978 .

[2]  Stephen Nickell,et al.  Biases in Dynamic Models with Fixed Effects , 1981 .

[3]  Jonathan N. Katz,et al.  Random Coefficient Models for Time-Series—Cross-Section Data: Monte Carlo Experiments , 2004, Political Analysis.

[4]  G. Garrett,et al.  Partisan Politics in the Global Economy , 1998 .

[5]  G. King,et al.  What to Do about Missing Values in Time‐Series Cross‐Section Data , 2010 .

[6]  P. J. Huber.  The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .

[7]  C. Granger,et al.  Co-integration and error correction: representation, estimation and testing , 1987 .

[8]  Nathaniel Beck,et al.  Estimating Dynamic Models is Not Merely a Matter of Technique , 1986 .

[9]  Cheng Hsiao,et al.  Formulation and estimation of dynamic models using panel data , 1982 .

[10]  C. Granger,et al.  Spurious regressions in econometrics , 1974 .

[11]  Deborah Mitchell,et al.  Globalization, government spending and taxation in the OECD , 2001 .

[12]  Roderick J. A. Little,et al.  Statistical Analysis with Missing Data , 1988 .

[13]  Grayham E. Mizon,et al.  The encompassing approach in econometrics , 1984 .

[14]  Nathaniel Beck,et al.  Throwing Out the Baby with the Bath Water: A Comment on Green, Kim, and Yoon , 2001, International Organization.

[15]  Andrew T. Levin,et al.  Unit root tests in panel data: asymptotic and finite-sample properties , 2002 .

[16]  R. Michael Alvarez,et al.  Aggregation and Dynamics of Survey Responses: The Case of Presidential Approval , 2000 .

[17]  James D. Hamilton.  Time Series Analysis , 1994 .

[18]  Nathaniel Beck,et al.  Nuisance vs. Substance: Specifying and Estimating Time-Series-Cross-Section Models , 1996, Political Analysis.

[19]  Nathaniel Beck,et al.  Comparing Dynamic Specifications: The Case of Presidential Approval , 1991, Political Analysis.

[20]  Alexander Hicks,et al.  Development and Crisis of the Welfare State: Parties and Policies in Global Markets. By Evelyne Huber and John D. Stephens. Chicago: University of Chicago Press, 2001. 368p. $54.00 cloth, $18.00 paper. , 2002, American Political Science Review.

[21]  Jan F. Kiviet,et al.  On bias, inconsistency and efficiency of various estimators in dynamic panel data models , 1995 .

[22]  Nathaniel Beck,et al.  Throwing Out the Baby with the Bath Water: A Comment on Green, Yoon and Kim , 2000 .

[23]  M. Pesaran,et al.  Testing for unit roots in heterogeneous panels , 2003 .

[24]  Jonathan N. Katz,et al.  8. Nathaniel Beck and Jonathan N. Katz. 1995. “What to Do (and Not to Do) with Time-Series Cross-Section Data.” American Political Science Review 89 (September): 634–47 Cited 398 times. , 2006, American Political Science Review.

[25]  Luke Keele,et al.  Taking Time Seriously: Dynamic Regression Models ⁄ , 2006 .

[26]  M. Arellano,et al.  Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations , 1991 .

[27]  Nathaniel L. Beck,et al.  The Methodology of Cointegration , 1992, Political Analysis.

[28]  Kristian Skrede Gleditsch,et al.  Space Is More than Geography: Using Spatial Econometrics in the Study of Political Economy , 2006 .

[29]  W. Newey,et al.  A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix , 1986 .

[30]  Robert J. Franzese,et al.  Spatial Econometric Models of Cross-Sectional Interdependence in Political Science Panel and Time-Series-Cross-Section Data , 2007, Political Analysis.

[31]  Luke Keele,et al.  Taking Time Seriously , 2008 .

[32]  Nathaniel Beck,et al.  Taking Time Seriously: Time-Series-Cross-Section Analysis with a Binary Dependent Variable , 1998 .

[33]  Luke Keele,et al.  Dynamic Models for Dynamic Theories: The Ins and Outs of Lagged Dependent Variables , 2006, Political Analysis.

[34]  James A. Stimson.  Regression in Space and Time: A Statistical Essay , 1985 .

[35]  Nathaniel Beck,et al.  Time‐series–cross‐section Data , 2001 .

[36]  Douglas A. Hibbs,et al.  Problems of Statistical Estimation and Causal Inference in Time-Series Regression Models , 1973 .

[37]  Ann L. Owen,et al.  Estimating dynamic panel data models: a guide for , 1999 .

[38]  David F. Hendry,et al.  Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England. , 1978 .

[39]  W. Newey,et al.  A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix , 1986 .