Policy and the structure of roll call voting in the US house

2020 ◽  
pp. 1-25
Author(s):  
Scott de Marchi ◽  
Spencer Dorsey ◽  
Michael J. Ensley
Keyword(s):  
House Of Representatives ◽  
Predictive Power ◽  
Topic Model ◽  
Roll Call ◽  
Congressional Committees ◽  
Machine Learning Approach ◽  
The Us ◽  
Out Of Sample ◽  
Alternative Measures ◽  
Ideological Dimension

Abstract Competition in the US Congress has been characterised along a single, left-right ideological dimension. We challenge this characterisation by showing that the content of legislation has far more predictive power than alternative measures, most notably legislators’ ideological positions derived from scaling roll call votes. Using a machine learning approach, we identify a topic model for final passage votes in the 111th through the 113th House of Representatives and conduct out-of-sample tests to evaluate the predictive power of bill topics relative to other measures. We find that bill topics and congressional committees are important for predicting roll call votes but that other variables, including member ideology, lack predictive power. These findings raise serious doubts about the claim that congressional politics can be boiled down to competition along a single left-right continuum and shed new light on the debate about levels of polarisation in Congress.

scholarly journals Does debt ceiling and government shutdown help in forecasting the us equity risk premium?

2016 ◽  
Vol 63 (3) ◽  
pp. 273-291 ◽  
Author(s):  
Goodness Aye ◽  
Frederick Deale ◽  
Rangan Gupta
Keyword(s):  
Risk Premium ◽  
Predictive Power ◽  
The United States ◽  
Equity Risk Premium ◽  
Equity Risk ◽  
The Us ◽  
Out Of Sample ◽  
Debt Ceiling ◽  
The Individual ◽  
Government Shutdown

This article evaluates the predictability of the equity risk premium in the United States by comparing the individual and complementary predictive power of macroeconomic variables and technical indicators using a comprehensive set of 16 economic and 14 technical predictors over a monthly out-ofsample period of 1995:01 to 2012:12 and an in-sample period of 1986:01- 1994:12. In order to do so we consider, in addition to the set of variables used in Christopher J. Neely et al. (2013) and using a more recent dataset, the forecasting ability of two other important variables namely government shutdown and debt ceiling. Our results show that one of the newly added variables namely government shutdown provides statistically significant out-of-sample predictive power over the equity risk premium relative to the historical average. Most of the variables, including government shutdown, also show significant economic gains for a risk averse investor especially during recessions.

scholarly journals What Goliaths and Davids among Swiss firms tell us about expected returns on Swiss asset markets

2019 ◽  
Vol 155 (1) ◽  
Author(s):  
David R. Haab ◽  
Thomas Nitschka
Keyword(s):  
Stock Market ◽  
Predictive Power ◽  
Bond Market ◽  
Asset Markets ◽  
Market Returns ◽  
Stock Market Returns ◽  
Asset Return ◽  
The Us ◽  
Out Of Sample ◽  
Sample Test

AbstractMotivated by recent US evidence, we evaluate the predictive power of changes in the weight of large firms in the aggregate stock market (“Goliath vs David” (GVD)) for Swiss stock market returns and bond market returns. Previous research suggests that the asset return dynamics in the US and Switzerland differ markedly. Forecasting Swiss asset returns hence constitutes a challenging “out-of-sample” test for GVD. Over the sample period from January 1999 to December 2017, we find that the Swiss version of GVD exhibits predictive power for Swiss stock and bond market returns even in the presence of global predictors. However, Swiss bond market returns are best predicted by the US term spread.

Interaction of Ukrainian Diaspora and the USA Government Regarding Celebration of Ukrainian Independence Day on January 22

2018 ◽  
Vol 1 (47) ◽  
pp. 136-145
Author(s):  
Halyna Shchyhelska
Keyword(s):  
United States ◽  
House Of Representatives ◽  
The United States ◽  
100Th Anniversary ◽  
Totalitarian Regime ◽  
The Public ◽  
Us Congress ◽  
The Us ◽  
Public Consciousness ◽  
The Usa

2018 marks the 100th anniversary of the proclamation of Ukrainian independence. OnJanuary 22, 1918, the Ukrainian People’s Republic proclaimed its independence by adopting the IV Universal of the Ukrainian Central Rada, although this significant event was «wiped out» from the public consciousness on the territory of Ukraine during the years of the Soviet totalitarian regime. At the same time, January 22 was a crucial event for the Ukrainian diaspora in the USA. This article examines how American Ukrainians interacted with the USA Government institutions regarding the celebration and recognition of the Ukrainian Independence day on January 22. The attention is focused on the activities of ethnic Ukrainians in the United States, directed at the organization of the special celebration of the Ukrainian Independence anniversaries in the US Congress and cities. Drawing from the diaspora press and Congressional Records, this article argues that many members of Congress participated in the observed celebration and expressed kind feelings to the Ukrainian people, recognised their fight for freedom, during the House of Representatives and Senate sessions. Several Congressmen submitted the resolutions in the US Congress urging the President of United States to designate January 22 as «Ukrainian lndependence Day». January 22 was proclaimed Ukrainian Day by the governors of fifteen States and mayors of many cities. Keywords: January 22, Ukrainian independence day, Ukrainian diaspora, USA, interaction, Congress

scholarly journals German forecasters’ narratives: How informative are German business cycle forecast reports?

2021 ◽  
Author(s):  
Karsten Müller
Keyword(s):  
Business Cycle ◽  
Fixed Effects ◽  
Predictive Power ◽  
Recursive Estimation ◽  
Regression Methods ◽  
Inflation Forecasts ◽  
Fixed Effects Panel Regression ◽  
Weak Evidence ◽  
Out Of Sample ◽  
Different Characteristics

AbstractBased on German business cycle forecast reports covering 10 German institutions for the period 1993–2017, the paper analyses the information content of German forecasters’ narratives for German business cycle forecasts. The paper applies textual analysis to convert qualitative text data into quantitative sentiment indices. First, a sentiment analysis utilizes dictionary methods and text regression methods, using recursive estimation. Next, the paper analyses the different characteristics of sentiments. In a third step, sentiment indices are used to test the efficiency of numerical forecasts. Using 12-month-ahead fixed horizon forecasts, fixed-effects panel regression results suggest some informational content of sentiment indices for growth and inflation forecasts. Finally, a forecasting exercise analyses the predictive power of sentiment indices for GDP growth and inflation. The results suggest weak evidence, at best, for in-sample and out-of-sample predictive power of the sentiment indices.

On enlarging the US House of Representatives

1998 ◽  
Vol 17 (3) ◽  
pp. 319-329 ◽  
Author(s):  
Jonathan I. Leib ◽  
Gerald R. Webster
Keyword(s):  
House Of Representatives ◽  
The Us

scholarly journals The integrative force of political institutions? Direct democracy and voter turnout across ethnic and nativity groups

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Anita Manatschal
Keyword(s):  
Voter Turnout ◽  
Political Institutions ◽  
Direct Democracy ◽  
First Generation ◽  
The Us ◽  
Alternative Measures ◽  
Hispanic Voters ◽  
Democratic Elections ◽  
Positive Effect ◽  
Shed Light

AbstractMuch has been written on the positive effect of direct democracy (initiatives, referendums) on voter turnout. However, we have limited knowledge about potential differential effects on voters belonging to various ethnic groups. The paper argues that depending on a group’s responsiveness to the political context, direct democracy can (dis-)integrate voters (from) into the electorate. Empirical analysis of Current Population Survey (CPS) voting supplement survey data, together with data on the absolute use of direct democracy across US states, corroborates this theoretical expectation, however lending more support for the disintegrating assumption. Frequent direct democratic elections further widen the negative voting gap between first-generation Asian voters and voters living in the US for three generations or longer, whereas they tend to diminish this voting gap for first-generation Hispanic voters. The disintegrative pattern for first-generation Asian voters remains even significant when excluding California from the state sample, yet not the integrative tendency for first-generation Hispanics. Additional analyses using alternative measures of direct democracy and voting, and applying statistical adjustments to address causality concerns, confirm the robustness of these findings, which shed light on the so-far underexplored (dis-)integrative potential of political institutions.

scholarly journals Applying Heath-Jarrow-Morton Model to Forecasting the US Treasury Daily Yield Curve Rates

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 114
Author(s):  
Valerii Maltsev ◽  
Michael Pokojovy
Keyword(s):  
Predictive Power ◽  
Yield Curve ◽  
Real Data ◽  
Stochastic Evolution ◽  
Infinite Dimensions ◽  
No Arbitrage ◽  
Hjm Model ◽  
Concise Review ◽  
The Us ◽  
Modeling And Forecasting

The Heath-Jarrow-Morton (HJM) model is a powerful instrument for describing the stochastic evolution of interest rate curves under no-arbitrage assumption. An important feature of the HJM approach is the fact that the drifts can be expressed as functions of respective volatilities and the underlying correlation structure. Aimed at researchers and practitioners, the purpose of this article is to present a self-contained, but concise review of the abstract HJM framework founded upon the theory of interest and stochastic partial differential equations in infinite dimensions. To illustrate the predictive power of this theory, we apply it to modeling and forecasting the US Treasury daily yield curve rates. We fit a non-parametric model to real data available from the US Department of the Treasury and illustrate its statistical performance in forecasting future yield curve rates.

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