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Book part
Publication date: 13 December 2013

Eugene Choo and Shannon Seitz

We develop and estimate an empirical collective model with endogenous marriage formation, participation, and family labor supply. Intra-household transfers arise…

Abstract

We develop and estimate an empirical collective model with endogenous marriage formation, participation, and family labor supply. Intra-household transfers arise endogenously as the transfers that clear the marriage market. The intra-household allocation can be recovered from observations on marriage decisions. Introducing the marriage market in the collective model allows us to independently estimate transfers from labor supplies and from marriage decisions. We estimate a semiparametric version of our model using 1980, 1990, and 2000 US Census data. Estimates of the model using marriage data are much more consistent with the theoretical predictions than estimates derived from labor supply.

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Structural Econometric Models
Type: Book
ISBN: 978-1-78350-052-9

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Article
Publication date: 26 September 2008

Yener Altunbas¸s, Antonis Karagiannis, Ming‐Hua Liu and Alireza Tourani‐Rad

The purpose of this paper is to investigate the profitability of European Union (EU) firms with the aim of confirming the mean‐reverting pattern documented by earlier…

Abstract

Purpose

The purpose of this paper is to investigate the profitability of European Union (EU) firms with the aim of confirming the mean‐reverting pattern documented by earlier research in the USA. In addition, the paper classifies firms by industry sectors across countries to investigate potential differences.

Design/methodology/approach

The paper follows closely a model where the forecasting of profitability is done through year‐by‐year regressions. This approach allows the use of large samples and the year‐by‐year variation in the slopes. Both a linear and a nonlinear partial adjustment models are used for forecasting profitability.

Findings

Findings show that the profitability does follow a mean‐reverting process and that profitability forecasting can be improved substantially by exploiting the mean‐reverting feature. Further analysis shows that mean reversion does not play an important role in EU countries as in the USA and there is no evidence of nonlinearity in mean reversion. It was also found that mean‐reverting speed differ across industries, with utilities, financial and manufacturing among the lowest.

Research limitations/implications

The sample companies are not originated from a single economy, but from 15 different countries with different macro‐economic conditions that might influence their profitability.

Originality/value

Studying the European market, where the institutional and financial structure of firms are different from the USA allows us to observe whether the US results are sample specific or can be generalized and applied elsewhere. The difference observed in these sample results is probably due to the fact that the US economy is more competitive than that of EU.

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Managerial Finance, vol. 34 no. 11
Type: Research Article
ISSN: 0307-4358

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Book part
Publication date: 16 December 2009

Zongwu Cai, Jingping Gu and Qi Li

There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent…

Abstract

There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.

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Nonparametric Econometric Methods
Type: Book
ISBN: 978-1-84950-624-3

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Book part
Publication date: 19 December 2012

Shahram Amini, Michael S. Delgado, Daniel J. Henderson and Christopher F. Parmeter

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which…

Abstract

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

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Essays in Honor of Jerry Hausman
Type: Book
ISBN: 978-1-78190-308-7

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Book part
Publication date: 1 January 2014

Javier Hidalgo and Jungyoon Lee

This paper examines a nonparametric CUSUM-type test for common trends in large panel data sets with individual fixed effects. We consider, as in Zhang, Su, and Phillips…

Abstract

This paper examines a nonparametric CUSUM-type test for common trends in large panel data sets with individual fixed effects. We consider, as in Zhang, Su, and Phillips (2012), a partial linear regression model with unknown functional form for the trend component, although our test does not involve local smoothings. This conveniently forgoes the need to choose a bandwidth parameter, which due to a lack of a clear and sensible information criteria is difficult for testing purposes. We are able to do so after making use that the number of individuals increases with no limit. After removing the parametric component of the model, when the errors are homoscedastic, our test statistic converges to a Gaussian process whose critical values are easily tabulated. We also examine the consequences of having heteroscedasticity as well as discussing the problem of how to compute valid critical values due to the very complicated covariance structure of the limiting process. Finally, we present a small Monte Carlo experiment to shed some light on the finite sample performance of the test.

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Essays in Honor of Peter C. B. Phillips
Type: Book
ISBN: 978-1-78441-183-1

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Article
Publication date: 17 August 2012

Mehir Baidya, Bipasha Maity and Kamal Ghose

The purpose of this study is to estimate the relative contributions of individual marketing mix variables to sales as well as short‐term and long‐term effects of…

Abstract

Purpose

The purpose of this study is to estimate the relative contributions of individual marketing mix variables to sales as well as short‐term and long‐term effects of advertising in India.

Design/methodology/approach

Time‐series data on sales and marketing mix variables have been collected for two brands. Two double‐log regression modes have been fitted on data to estimate the relative contribution of each effort as well as to isolate the amount of sales due to advertising only. In addition, a log‐linear partial‐adjustment model has been fitted on adjusted sales and advertising data to estimate both short‐term and long‐term effects of advertising.

Findings

Results reveal that all the marketing mix variables have significant relative contributions to sales in both the cases. It is also found that advertising does have significant short‐term and long‐term effects on adjusted sales for both the brands.

Practical implications

Findings provide a deep insight in dynamic perspective of advertising that make them eminently suitable in the process of allocation of budget to achieve both the short‐term and long‐term goals of advertising.

Originality/value

This research made a notable contribution to the literature due to lack of quantitative modeling works on marketing data reported in the field of advertising in India.

Details

Journal of Indian Business Research, vol. 4 no. 3
Type: Research Article
ISSN: 1755-4195

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Article
Publication date: 15 February 2016

Honglei Yan, Suigen Yang and shengmin zhao

The purpose of this paper is to study the pricing efficiency of convertible bonds and arbitrage opportunities between the convertible bonds and the underlying stocks thus…

Abstract

Purpose

The purpose of this paper is to study the pricing efficiency of convertible bonds and arbitrage opportunities between the convertible bonds and the underlying stocks thus improve market efficiency.

Design/methodology/approach

Using nonparametric fixed effect panel data model, the authors build pricing model of convertible bonds and obtain fitted value for them. Then the authors constructs simultaneous confidence band for the smooth function to identify mispricing and study the pricing efficiency and arbitrage opportunities of convertible bonds.

Findings

Result shows, convertible bonds’ prices largely depend on stock prices. Pricing efficiency does not improve during the past few years as there are quite a few trading opportunities. Arbitrage opportunities increase as the stock prices approach it maxima, and selling opportunities for convertible bonds surpass buying opportunities which indicates that investors use market neutral strategies to arbitrage. Pricing efficiencies varies a lot and it is affected by the features of the stocks and convertible bonds. Index stocks eligible for margin trading with high liquidity enjoy higher pricing efficiency.

Research limitations/implications

The study does not take into account trading cost and risk management measures.

Practical/implications

Arbitrage between the underlying and the convertible bonds is profitable and contributes to pricing efficiency therefore should be encouraged. The regulator should pay attention to the extreme mispricing of the underlying and convertible bonds which cannot be corrected by the market as there might be manipulation.

Originality/value

Since traditional pricing methods are based on the framework of non-arbitrage equilibrium with the assumption of balanced and perfect market, there are many restrictions in the pricing process and the practical utility is somewhat limited, and the impractical assumptions lead to model risk. This study uses nonparametric regression to study the pricing of convertible bonds thus circumvents the problem of model risk. Simultaneous confidence band for smooth function identifies mispricing and explicitly reflects the variation of pricing efficiency as well as signalizes trading opportunities. Application of nonparametric regression and simultaneous confidence band in derivative pricing is advantageous in accuracy and simplicity.

Details

China Finance Review International, vol. 6 no. 1
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 18 November 2019

Yulong Li, Jie Lin, Zihan Cui, Chao Wang and Guijun Li

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to…

Abstract

Purpose

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to calculate the workforce productivity changes of the US construction industry from 2006 to 2016, with the number of laborers as input and value of construction industry as output.

Design/methodology/approach

The present study introduced the data envelopment analysis (DEA) based Malmquist productivity index model to measure the workforce productivity of the US construction industry from 2006 to 2016.

Findings

The results indicated that the workforce productivity of the US construction industry experienced a continuous decline, except for the increases from 2011 to 2013 and from 2014 to 2015. It was also shown that there were gaps in the workforce productivity development level among all states and nine regions in the US construction industry. Besides, the relationship between workforce productivity and four aspects, including real estate price, workforce, climate distribution and economic factors, was analyzed.

Research limitations/implications

The calculation of the productivity of the US construction industry is based on the premise that the external environment is fixed and unchanged from 2006 to 2016, but the multi-level DEA model for further calculation is required for obtaining more effective conclusions.

Social implications

This paper measures the workforce productivity of the US construction industry over the past 11 years, which added latest analysis and knowledge into the construction industry, providing decision-makers with advice and data support to formulate policies to improve workforce productivity.

Originality/value

This study provided both government decision-makers and industrial practitioners with important macro background environment information, which will facilitate the improvement of workforce productivity in the construction industry in different regions of the US.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 1
Type: Research Article
ISSN: 0969-9988

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Book part
Publication date: 16 December 2009

Hector O. Zapata and Krishna P. Paudel

This is a survey paper of the recent literature on the application of semiparametric–econometric advances to testing for functional form of the environmental Kuznets curve…

Abstract

This is a survey paper of the recent literature on the application of semiparametric–econometric advances to testing for functional form of the environmental Kuznets curve (EKC). The EKC postulates that there is an inverted U-shaped relationship between economic growth (typically measured by income) and pollution; that is, as economic growth expands, pollution increases up to a maximum and then starts declining after a threshold level of income. This hypothesized relationship is simple to visualize but has eluded many empirical investigations. A typical application of the EKC uses panel data models, which allows for heterogeneity, serial correlation, heteroskedasticity, data pooling, and smooth coefficients. This vast literature is reviewed in the context of semiparametric model specification tests. Additionally, recent developments in semiparametric econometrics, such as Bayesian methods, generalized time-varying coefficient models, and nonstationary panels are discussed as fruitful areas of future research. The cited literature is fairly complete and should prove useful to applied researchers at large.

Details

Nonparametric Econometric Methods
Type: Book
ISBN: 978-1-84950-624-3

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Article
Publication date: 13 August 2018

Xinzhi Zhu, Shuo Yang, Jingyi Lin, Yi-Ming Wei and Weigang Zhao

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030…

Abstract

Purpose

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.

Design/methodology/approach

With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.

Findings

The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.

Originality/value

Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.

Details

Journal of Modelling in Management, vol. 13 no. 3
Type: Research Article
ISSN: 1746-5664

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