Feedback Effects in the Market Regulation of Bank Leverage: A Time-Series and Cross-Section Analysis

1980 ◽  
Vol 62 (2) ◽  
pp. 276 ◽  
Author(s):  
Brian C. Gendreau ◽  
David Burras Humphrey
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Market Regulation ◽  
Feedback Effects ◽  
Section Analysis

scholarly journals THE INFLUENCE OF BIASED SIGNAL SET ON STOCK MARKET—BASED ON THE SHANGHAI COMPOSITE INDEX

2021 ◽  
Author(s):  
ZE-LIN LIU
Keyword(s):  
Time Series ◽  
Stock Market ◽  
Time Series Analysis ◽  
Cross Section ◽  
Financial Market ◽  
High Weight ◽  
Composite Index ◽  
Signal Set ◽  
Low Weight ◽  
Section Analysis

Based on the two phenomena of over and underreaction, this paper introduces the characteristics of signal set into the model, which studies the price deviation of financial market caused by investors' signal set deviation. The text concludes that investors overreact to information of low weight and underreact to information of high weight, and uses cross-section analysis and time series analysis to verify the correctness of the results.

scholarly journals Determinantes políticos do déficit fiscal nos estados brasileiros (1987-1997)

2010 ◽  
Vol 18 (35) ◽  
pp. 131-149 ◽  
Author(s):  
Cristiane Batista ◽  
Ximena Simpson
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Standard Error ◽  
De Se ◽  
Pooled Time Series ◽  
Section Analysis

O objetivo do trabalho é analisar os determinantes do balanço fiscal nos estados brasileiros em um período de grande instabilidade da economia do país: as décadas de 1980 e 1990. O argumento principal do trabalho postula que, mesmo em um contexto de ajuste fiscal, fatores ligados à inclinação ideológica do chefe do poder Executivo estadual, à capacidade decisória do poder Legislativo nesse nível de governo, bem como a relação entre estados e governo federal são parâmetros fundamentais para o entendimento da situação fiscal da federação brasileira. A metodologia empregada para verificar o modelo teórico corresponde à análise econométrica de painel, também conhecida como séries agregadas (em inglês: pooled time series - cross section analysis), que nos permite considerar concomitantemente a dimensão espaço (estados) e a dimensão tempo (ano). Na estimação dos parâmetros do modelo, seguimos o método "panel corrected standard error" (OLS com erro padrão corrigido), sugerido por Beck e Katz para análises de painel de dimensões similares às do presente trabalho. Nossos resultados corroboram a previsão da importância de se considerar as subunidades da federação. As análises que buscam explicar o desempenho da administração macroeconômica nacional não podem deixar de levar em conta a relevância das instituições subnacionais e seu impacto na estrutura de incentivos dos atores envolvidos nos processos decisórios.

Party and the Dynamics of Congressional Committee Composition in the US House, 1947–96

2003 ◽  
Vol 33 (4) ◽  
pp. 659-679 ◽  
Author(s):  
GARRY YOUNG ◽  
VALERIE HEITSHUSEN
Keyword(s):  
Time Series ◽  
Temporal Variation ◽  
Cross Section ◽  
Spatial And Temporal Variation ◽  
Congressional Committee ◽  
Majority Party ◽  
The Us ◽  
Resource Levels ◽  
Section Analysis

Renewed scholarly interest in the role of US congressional parties has recently coincided with a continuing interest in legislative committee influence and the extent to which that influence relies on committee preference composition. We argue that majority party incentives to influence composition vary by committee salience and party margins. In turn, the party’s ability to influence composition of salient committees is constrained, but varies by party resource levels. We present data on committee composition for the 80th to 104th US Houses and test these expectations using time-series cross-section analysis. The evidence provides support for the predictions – which have been hypothesized or tested anecdotally but have not heretofore been systematically tested – explaining both spatial and temporal variation.

A Moving Cross-Section Analysis of Demand for Toothpaste

1970 ◽  
Vol 7 (4) ◽  
pp. 439-449 ◽  
Author(s):  
Kristian S. Palda ◽  
Larry M. Blair
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Least Squares ◽  
Cross Section ◽  
Single Equation ◽  
Cross Sectional ◽  
Least Squares Estimates ◽  
Section Analysis

MRCA panel data on toothpaste expenditures are used to demonstrate how time series and cross-sectional bias can be eliminated by the method of covariance regression from single-equation demand least squares estimates.

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