Journal of Risk and Financial Management

Research

16 pages, 273 KiB

Open AccessArticle

Minimum Wage Changes across Provinces in China: Average Treatment Effects on Employment and Investment Decisions

by Ji Luo and Daniel J. Henderson

J. Risk Financial Manag. 2021, 14(1), 22; https://doi.org/10.3390/jrfm14010022 - 5 Jan 2021

Viewed by 2098

We exploit data from the China Household Finance Survey to examine the impact of changes in the minimum wage on employment and investment decisions. We are able to non-parametrically identify the average treatment effect on the treated via exogenous variation in the minimum [...] Read more.

We exploit data from the China Household Finance Survey to examine the impact of changes in the minimum wage on employment and investment decisions. We are able to non-parametrically identify the average treatment effect on the treated via exogenous variation in the minimum wage across provinces. We find that changes in the minimum wage had no adverse effects on employment (in terms of days worked per month or hours worked per work day) but found evidence that changes in the minimum wage impacted the percentage of families that had a bank account, a family in a rural area owned their home, and whether families (whose highest level of education was primary school) planned to purchase a home. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

9 pages, 570 KiB

Open AccessArticle

Natural Disasters and Economic Growth: A Semiparametric Smooth Coefficient Model Approach

by Nikos Fatouros and Yiguo Sun

J. Risk Financial Manag. 2020, 13(12), 320; https://doi.org/10.3390/jrfm13120320 - 15 Dec 2020

Cited by 4 | Viewed by 3085

Abstract

Despite the fact that growth theories suggest that natural disasters should have an impact on economic growth, parametric empirical studies have provided little to no evidence supporting that prediction. On the other hand, pure nonparametric regression analysis would be an extremely difficult task [...] Read more.

Despite the fact that growth theories suggest that natural disasters should have an impact on economic growth, parametric empirical studies have provided little to no evidence supporting that prediction. On the other hand, pure nonparametric regression analysis would be an extremely difficult task due to the curse of dimensionality. We therefore re-investigate the impact of natural disasters on economic growth, applying a semiparametric smooth coefficient panel data model that takes into account fixed effects. Our study finds evidence that the coefficient curve of investment is a U-shaped function of the severity of the natural disasters. Thus, for relatively small disasters, marginal returns to investment decrease on the severity of natural disasters. However, after a certain threshold, the coefficient of investment starts increasing as natural disasters become more severe. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

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12 pages, 296 KiB

Open AccessArticle

Nonparametric Estimation of the Ruin Probability in the Classical Compound Poisson Risk Model

by Yuan Gao, Lingju Chen, Jiancheng Jiang and Honglong You

J. Risk Financial Manag. 2020, 13(12), 298; https://doi.org/10.3390/jrfm13120298 - 29 Nov 2020

Viewed by 1895

Abstract

In this paper we study estimating ruin probability which is an important problem in insurance. Our work is developed upon the existing nonparametric estimation method for the ruin probability in the classical risk model, which employs the Fourier transform but requires smoothing on [...] Read more.

In this paper we study estimating ruin probability which is an important problem in insurance. Our work is developed upon the existing nonparametric estimation method for the ruin probability in the classical risk model, which employs the Fourier transform but requires smoothing on the density of the sizes of claims. We propose a nonparametric estimation approach which does not involve smoothing and thus is free of the bandwidth choice. Compared with the Fourier-transformation-based estimators, our estimators have simpler forms and thus are easier to calculate. We establish asymptotic distributions of our estimators, which allows us to consistently estimate the asymptotic variances of our estimators with the plug-in principle and enables interval estimates of the ruin probability. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

23 pages, 436 KiB

Open AccessArticle

The Environmental Kuznets Curve: A Semiparametric Approach with Cross-Sectional Dependence

by Alexandra Soberon and Irene D’Hers

J. Risk Financial Manag. 2020, 13(11), 292; https://doi.org/10.3390/jrfm13110292 - 23 Nov 2020

Cited by 11 | Viewed by 3132

Abstract

This paper proposes a new approach to examine the relationship between CO

_{2}

emissions and economic developing. In particular, we propose to test the Environmental Kuznets Curve (EKC) hypothesis for a panel of 24 OECD countries and 32 non-OECD countries by developing a [...] Read more.

This paper proposes a new approach to examine the relationship between CO

_{2}

emissions and economic developing. In particular, we propose to test the Environmental Kuznets Curve (EKC) hypothesis for a panel of 24 OECD countries and 32 non-OECD countries by developing a more flexible estimation technique which enables to account for functional form misspecification, cross-sectional dependence, and heterogeneous relationships among variables, simultaneously. We propose a new nonparametric estimator that extends the well-known Common Correlated Effect (CCE) approach from a fully parametric framework to a semiparametric panel data model. Our results corroborates that the nature and validity of the income–pollution relationship based on the EKC hypothesis depends on the model assumptions about the functional form specification. For all the countries analyzed, the proposed semiparametric estimator leads to non-monotonically increasing or decreasing relationships for CO

_{2}

emissions, depending on the level of economic development of the country. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

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24 pages, 405 KiB

Open AccessArticle

Propensity Score Weighting with Mismeasured Covariates: An Application to Two Financial Literacy Interventions

by Hao Dong and Daniel L. Millimet

J. Risk Financial Manag. 2020, 13(11), 290; https://doi.org/10.3390/jrfm13110290 - 21 Nov 2020

Cited by 1 | Viewed by 2366

Abstract

Estimation of the causal effect of a binary treatment on outcomes often requires conditioning on covariates to address selection concerning observed variables. This is not straightforward when one or more of the covariates are measured with error. Here, we present a new semi-parametric [...] Read more.

Estimation of the causal effect of a binary treatment on outcomes often requires conditioning on covariates to address selection concerning observed variables. This is not straightforward when one or more of the covariates are measured with error. Here, we present a new semi-parametric estimator that addresses this issue. In particular, we focus on inverse propensity score weighting estimators when the propensity score is of an unknown functional form and some covariates are subject to classical measurement error. Our proposed solution involves deconvolution kernel estimators of the propensity score and the regression function weighted by a deconvolution kernel density estimator. Simulations and replication of a study examining the impact of two financial literacy interventions on the business practices of entrepreneurs show our estimator to be valuable to empirical researchers. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

12 pages, 478 KiB

Open AccessArticle

A Hausman Test for Partially Linear Models with an Application to Implied Volatility Surface

by Yixiao Jiang

J. Risk Financial Manag. 2020, 13(11), 287; https://doi.org/10.3390/jrfm13110287 - 19 Nov 2020

Cited by 1 | Viewed by 2837

Abstract

This paper develops a test that helps assess whether the term structure of option implied volatility is constant across different levels of moneyness. The test is based on the Hausman principle of comparing two estimators, one that is efficient but not robust to [...] Read more.

This paper develops a test that helps assess whether the term structure of option implied volatility is constant across different levels of moneyness. The test is based on the Hausman principle of comparing two estimators, one that is efficient but not robust to the deviation being tested, and one that is robust but not as efficient. Distribution of the proposed test statistic is investigated in a general semiparametric setting via the multivariate Delta method. Using recent S&P 500 index traded options data from September 2009 to December 2018, we find that a partially linear model permitting a flexible “volatility smile” and an additive quadratic time effect is a statistically adequate depiction of the implied volatility data for most years. The constancy of implied volatility term structure, in turn, implies that option traders shall feel confident and execute volatility-based strategies using at-the-money options for its high liquidity. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

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10 pages, 239 KiB

Open AccessArticle

The Determinants of the Performance of Precious Metal Mutual Funds

by Ioannis E. Tsolas

J. Risk Financial Manag. 2020, 13(11), 286; https://doi.org/10.3390/jrfm13110286 - 18 Nov 2020

Cited by 3 | Viewed by 2251

Abstract

The aim of this paper is to assess the efficiency of a set of 62 precious metal mutual funds (PMMFs) and to explain performance differences between funds using weighted additive data envelopment analysis (DEA) and Tobit regression, respectively. The contribution of this paper [...] Read more.

The aim of this paper is to assess the efficiency of a set of 62 precious metal mutual funds (PMMFs) and to explain performance differences between funds using weighted additive data envelopment analysis (DEA) and Tobit regression, respectively. The contribution of this paper is twofold: to provide for the first-time metrics of the relative performance of PMMFs using a particular weighted additive model, namely the range-adjusted measure (RAM), and to explain the performance of the funds by the use of a Tobit model. Results do not suggest positive linkages between RAM-based and standard fund performance metrics (Sharpe ratio and Jensen’s alpha). Moreover, for the sample inefficient funds the mean–variance performance hypothesis does not hold. In addition, fund performance based on RAM can be explained by the persistence of the fund and the beta coefficient. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

26 pages, 444 KiB

Open AccessArticle

The Environmental Kuznets Curve with Recycling: A Partially Linear Semiparametric Approach

by Myrto Kasioumi and Thanasis Stengos

J. Risk Financial Manag. 2020, 13(11), 274; https://doi.org/10.3390/jrfm13110274 - 10 Nov 2020

Cited by 13 | Viewed by 3892

Abstract

This paper is the first to study a comparatively new Environmental Kuznets Curve which traces empirically the relationship between environmental abatement and real GDP. Our model is a partial linear semi parametric model that allows for two way fixed effects to eliminate the [...] Read more.

This paper is the first to study a comparatively new Environmental Kuznets Curve which traces empirically the relationship between environmental abatement and real GDP. Our model is a partial linear semi parametric model that allows for two way fixed effects to eliminate the bias arising from two sources. We use data for recycling and real GDP, for fifty states of the United States for the years between 1988 and 2017. We find evidence that this relationship is characterized by an increasing curve which confirms the existence of a J curve, a finding that agrees with the predictions from recent theoretical models. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

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25 pages, 861 KiB

Open AccessArticle

Higher-Order Risk–Returns to Education

by Daniel J. Henderson, Anne-Charlotte Souto and Le Wang

J. Risk Financial Manag. 2020, 13(11), 253; https://doi.org/10.3390/jrfm13110253 - 28 Oct 2020

Cited by 1 | Viewed by 2374

Abstract

In the traditional human capital framework, education is often considered as an investment, rather than consumption, while consumption is not necessarily precluded. Whether education is an investment is empirically unclear and relatively under-explored. We shed light on this issue by estimating the risk–return [...] Read more.

In the traditional human capital framework, education is often considered as an investment, rather than consumption, while consumption is not necessarily precluded. Whether education is an investment is empirically unclear and relatively under-explored. We shed light on this issue by estimating the risk–return trade-off in the context of education. If education is indeed an investment, risk could play an important role in individual educational decisions just as with risky assets. As portfolio theory predicts, there could be a trade-off between returns to education and risks concerning those returns: higher risks are generally associated with higher returns. We contribute to the literature by proposing various measures of risk based on the entire distribution of returns to education recovered by our nonparametric models. Our results confirm a trade-off between returns and variance. We also found statistically significant impacts for the higher moments: skewness and kurtosis. Interestingly, we found the relationship between mean returns and variance to be linear, and the relationship between expected returns and higher-moments (skewness and kurtosis) is non-linear. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

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13 pages, 268 KiB

Open AccessArticle

Shannon Entropy Estimation for Linear Processes

by Timothy Fortune and Hailin Sang

J. Risk Financial Manag. 2020, 13(9), 205; https://doi.org/10.3390/jrfm13090205 - 9 Sep 2020

Cited by 1 | Viewed by 2039

Abstract

In this paper, we estimate the Shannon entropy

S (f) = - E [log (f (x))]

of a one-sided linear process with probability density function

f (x)

. We employ the integral estimator [...] Read more.

In this paper, we estimate the Shannon entropy

S (f) = - E [log (f (x))]

of a one-sided linear process with probability density function

f (x)

. We employ the integral estimator

S_{n} (f)

, which utilizes the standard kernel density estimator

f_{n} (x)

of

f (x)

. We show that

S_{n} (f)

converges to

S (f)

almost surely and in

Ł^{2}

under reasonable conditions. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application II)

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