Abstract
We use the cross-section regression approach of Fama and MacBeth (1973) to construct cross-section factors corresponding to the time-series factors of Fama and French (2015). Time-series models that use only cross-section factors provide better descriptions of average returns than time-series models that use time-series factors. This is true when we impose constant factor loadings and when we use time-varying loadings that are natural for time-series factors and time-varying loadings that are natural for cross-section factors.
Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
AbstractOne of the main ways we try to understand the COVID-19 pandemic is through time series cross section counts of cases and deaths. Observational studies based on these kinds of data have concrete and well known methodological issues that suggest significant caution for both consumers and produces of COVID-19 knowledge. We briefly enumerate some of these issues in the areas of measurement, inference, and interpretation.
AbstractIn this paper, we investigate the dynamic link between recessions and stock market liquidity by examining the predictive content of illiquidity for US recessions. After controlling for other commonly featured recession predictors such as term spreads and credit spreads, we find that the illiquidity measure proposed by (Amihud, Y. 2002. “Illiquidity and Stock Returns: Cross-Section and Time-Series Effects.”
Carter and Signorino (2010) (hereinafter “CS”) add another arrow, a simple cubic polynomial in time, to the quiver of the binary time series—cross-section data analyst; it is always good to have more arrows in one's quiver. Since comments are meant to be brief, I will discuss here only two important issues where I disagree: are cubic duration polynomials the best way to model duration dependence and whether we can substantively interpret duration dependence.
The New Politics of the welfare state suggests that periods of welfare retrenchment present policymakers with a qualitatively different set of challenges and electoral incentives compared to periods of welfare expansion. An unresolved puzzle for this literature is the relative electoral success of retrenching governments in recent decades, as evidenced by various studies on fiscal consolidations. This article points to the importance of partisan biases as the main explanatory factor. I argue that partisan biases in the electorate create incentives for incumbent governments to depart from their representative function and push the burden of retrenchment on the very constituencies to which they owe their electoral mandate (‘Nixon-goes-to-China’). After offering a simple model on the logic of partisan biases, the article proceeds by testing the unexpected partisan hypotheses that the model generates. My findings from a cross-section time-series analysis in a set of 23 OECD countries provide corroborative evidence on this Nixon-goes-to-China logic of welfare retrenchment: governments systematically inflict pain on their core constituencies. These effects are especially pronounced in periods of severe budgetary pressure.
Penelititan ini bertujuan mengetahui dan menganalisis pengaruh Perencanaan Pajak (Tax Planning) dan Penghindaran Pajak (Tax Avoidance) terhadap Nilai Perusahaan pada perusahaan manufaktur sektor industri konsumsi subsektor makanan dan minuman yang terdaftar di Bursa Efek Indonesia Tahun 2017-2019. Menggunakan data sekunder dan metode penelitian kuantitatif. Teknik analisis yang digunakan yaitu regresi data panel, gabungan time series dan cross section. Menggunakan aplikasi pengolahan data Eviews 10 untuk memperoleh gambaran yang menyeluruh mengenai hubungan antara antara variabel satu dengan variabel lainnya. Sampel yang digunakan sebanyak 16 perusahaan manufaktur sektor industri barang konsumsi subsektor makanan dan minuman selama 3 periode dari tahun 2017-2019 dengan purposive sampling sebagaiimetode pengambilan sampel. Hasillpenelitian menunjukkan bahwa Perencanaan Pajak (BTD) berpengaruh positif dan tidak signifikan terhadap nilai perusahaan (PBV) dan penghindaran Pajak (ETR) berpengaruh negatiffdan tidak signifikan terhadap nilai perusahaan.
Comparing Cross-Section and Time-Series Factor Models