LIFE-CYCLE INCOME HYPOTHESIS AND DEMOGRAPHIC STRUCTURE: A SEMI-NONPARAMETRIC ANALYSIS USING A PANEL OF COUNTRIES

2013 ◽  
Vol 58 (01) ◽  
pp. 1350003
Author(s):  
CHEOLBEOM PARK ◽  
JINA YU
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Life Cycle ◽  
Response Function ◽  
Demographic Structure ◽  
Cross Sectional ◽  
Nonparametric Approach ◽  
Savings Rate ◽  
High Level ◽  
Sectional Analysis

In this paper, we attempt to determine whether the life-cycle income (LCI) hypothesis can explain movements in the national savings rate using the panel data of countries and the semi-nonparametric approach. While relating movements in the population density function to movements in the national savings rate, we are able to estimate the age response function with a high level of precision, and the estimated age response function is hump-shaped, which is generally consistent with the prediction from the LCI hypothesis. Running time-series regressions separately for individual countries, we also demonstrate that the estimated age response functions are consistent with the LCI hypothesis in a large proportion of countries, despite limited observations in a variety of countries. Finally, our time-series and cross-sectional analysis results imply that the LCI hypothesis is more likely to hold in a country wherein the growth rate of per capita GDP and the growth rate of population are high.

The Initial Return and Its Conditional Return Volatility: Evidence from the Chinese IPO Market

2014 ◽  
Vol 17 (04) ◽  
pp. 1450022 ◽  
Author(s):  
M. Monica Hussein ◽  
Zhong-Guo Zhou
Keyword(s):  
Time Series ◽  
Linear Functions ◽  
Return Volatility ◽  
Cross Sectional ◽  
Variance Model ◽  
Initial Return ◽  
Traditional Market ◽  
Mean And Variance ◽  
The Mean ◽  
Sectional Analysis

This paper investigates the monthly initial return and its conditional return volatility for Chinese IPOs. We find that the mean initial return (IR) and cross-sectional return volatility are highly auto- and cross-correlated, and time-varying. We propose a system of two simultaneous equations: a GARCH-in-mean (GARCH-M) process with an ARMA(1,1) adjustment in the residuals for the IR and an EGARCH process for the conditional return volatility, assuming that the IR and its conditional return volatility are linear functions of the same market, firm- and offer-specific characteristics. We find that the model captures both time-series and cross-sectional correlations at the mean and variance levels. Our findings suggest that the conditional return volatility affects the IR positively and significantly, in addition to the traditional market, firm- and offer-specific characteristics. IPOs with higher conditional return volatility, as a proxy for information asymmetry, tend to be underpriced more. The paper demonstrates the merit of using a conditional variance model, along with time series and cross-sectional analysis to price Chinese IPOs.

The influence of welfare state factors on nursing professionalization and nursing human resources: A time‐series cross‐sectional analysis, 2000–2015

2019 ◽  
Vol 75 (11) ◽  
pp. 2797-2810 ◽  
Author(s):  
Virginia Gunn ◽  
Carles Muntaner ◽  
Edwin Ng ◽  
Michael Villeneuve ◽  
Montserrat Gea‐Sanchez ◽  
...  
Keyword(s):  
Time Series ◽  
Human Resources ◽  
Welfare State ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Sectional Analysis

scholarly journals International Migration and Turnout Bias

2019 ◽  
Vol 53 (1) ◽  
pp. 33-38
Author(s):  
Michael J. Wigginton ◽  
Daniel Stockemer ◽  
Jasmine van Schouwen
Keyword(s):  
Time Series ◽  
International Migration ◽  
Potential Bias ◽  
Cross Sectional ◽  
Cross Sectional Analysis ◽  
Percentage Points ◽  
Voting Age ◽  
Migration Flows ◽  
Registered Voters ◽  
Sectional Analysis

ABSTRACTThis article focuses on two commonly used indicators of turnout, VAP turnout (the number of votes cast as a percentage of the voting-age population) and RV turnout (votes cast as a percentage of the number of registered voters), and discusses possible biases induced by migration flows. Using a global dataset on elections in more than 100 democracies between 1990 and 2012, we tested the potential bias induced by the percentage of resident noncitizens and nationals living abroad on VAP and RV turnout, respectively. Through time-series cross-sectional analysis, we found that the number of resident noncitizens negatively biases VAP turnout, to the extent that a country with 10% noncitizen residents would have turnout underreported by nearly 4 percentage points. In contrast, we found that the number of nationals living abroad does not induce a turnout bias.

scholarly journals Trade and Redistribution

2019 ◽  
Author(s):  
Lucy Barnes
Keyword(s):  
Time Series ◽  
World War I ◽  
Trade Policy ◽  
Free Trade ◽  
World War ◽  
Cross Sectional ◽  
Progressive Taxation ◽  
Tax Progressivity ◽  
Trade Politics ◽  
Sectional Analysis

What explains variation in tax progressivity before World War I? I argue that trade politics shaped the emergence of progressive taxation. If labor could provide a useful ally, trade policy coalitions meant compromise on redistributive demands: progressive taxes, especially where inequality was lower. In time-series cross-sectional analysis, I find that trade interest proximity between labor and elites was associated with more progressive taxation in ten European countries between 1870 and 1913 under conditions of low inequality. The coalition and compromise mechanism is evident in subnational evidence from Britain. Where constituency interests favored free trade, Liberal-Labour electoral alliance was more likely in 1906, and the local MP was more likely to support the 1909 `People's Budget' for progressive taxation.

The Determinants of Idiosyncratic Volatility

2017 ◽  
Vol 25 (4) ◽  
pp. 509-545
Author(s):  
Jaeuk Khil ◽  
Song Hee Kim ◽  
Eun Jung Lee
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Cross Section ◽  
Growth Rates ◽  
Idiosyncratic Volatility ◽  
Return Volatility ◽  
Firm Level ◽  
Cross Sectional ◽  
Asset Growth ◽  
The Cross

We investigate the cross-sectional and time-series determinants of idiosyncratic volatility in the Korean market. In particular, we focus on the empirical relation between firms’ asset growth rate and idiosyncratic stock return volatility. We find that, in the cross-section, companies with high idiosyncratic volatility tend to be small and highly leveraged, have high variance of ROE and Market to Book ratio, high turnover rate, and pay no dividends. Furthermore, firms with extreme (either high positive or negative) asset growth rates have high idiosyncratic return volatility than firms with moderate growth rates, suggesting the V-shaped relation between asset growth rate and idiosyncratic return volatility. We find that the V-shaped relation is robust even after controlling for other factors. In time-series, we find that firm-level idiosyncratic volatility is positively related to the dispersion of the cross-sectional asset growth rates. As a result, this study is contributed to show that the asset growth is the most important predictor of firm-level idiosyncratic return volatility in both the cross-section and the time-series in the Korean stock market. In addition, we show how the effect of risk factors varies with industries.

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