Search results for "quantile regression."
showing 10 items of 64 documents
A new approach for clustering of effects in quantile regression
2017
In this paper we aim at nding similarities among the coefficients from a multivariate regression. Using a quantile regression coefficients modeling, the effect of each covariate, given a response (also multivariate) is a curve in the multidimensional space of the percentiles. Collecting all the curves, describing the effects of each covariate on each response variable, we could be able to assess if only one or more covariates have same effects on different responses.
Quantile regression for the FDI gravity equation
2015
Abstract Firm-level heterogeneity shapes foreign direct investment (FDI) flows, whereby a few firms are responsible for most of the world's FDI. Aggregate outcomes of FDI are highly skewed, and the estimates of FDI's antecedents vary largely depending on FDI level. The incidence of individual firms, however, varies across FDI's quantiles. To study the individual firms' effect on FDI flows, this study develops a quantile regression method for bilateral FDI panel data. This study estimates the differential incidence of individual firm-level projects on aggregate flows among 161 countries from 2003 to 2012. Results suggest that FDI's determinants vary across quantiles. In particular, the effec…
A penalized approach to covariate selection through quantile regression coefficient models
2019
The coefficients of a quantile regression model are one-to-one functions of the order of the quantile. In standard quantile regression (QR), different quantiles are estimated one at a time. Another possibility is to model the coefficient functions parametrically, an approach that is referred to as quantile regression coefficients modeling (QRCM). Compared with standard QR, the QRCM approach facilitates estimation, inference and interpretation of the results, and generates more efficient estimators. We designed a penalized method that can address the selection of covariates in this particular modelling framework. Unlike standard penalized quantile regression estimators, in which model selec…
NEIGHBORHOOD EFFECTS IN SPATIAL HOUSING VALUE MODELS. THE CASE OF THE METROPOLITAN AREA OF PARIS (1999)
2009
In hedonic housing models, the spatial dimension of housing values are traditionally processed by the impact of neighborhood variables and accessibility variables. In this paper we show that spatial effects might remain once neighborhood effects and accessibility have been controlled for. We notably stress on three sides of neighborhood effects: social capital, social status and social externalities and consider the accessibility to the primary economic center as describing the urban spatial trend. Using spatial econometrics specifications of the hedonic equation, we estimate whether spatial effects impact the housing values. Our empirical case concerns the Metropolitan Area (MA) of Paris i…
Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach
2015
This paper examines the degree of interest rate exposure of Spanish industries for the period 1993–2012 using the quantile regression methodology. The empirical results show that the Spanish stock market exhibits a significant level of interest rate sensitivity, although there are notable differences across industries and over time. In addition, the impact of changes in interest rates on industry equity returns tends to be more pronounced in extreme market conditions, i.e. during crises or bubbles in stock markets, than in normal periods. This finding may be related to herding behavior of stock investors during periods of market stress.
Carbon and safe-haven flows
2022
<abstract> <p>This paper explores the role of European Union Allowances (EUAs) as a safe haven for a range of assets and analyses the effect of safe-haven flows on the European carbon futures market. In particular, we demonstrate that EUAs can be considered a refuge against fluctuations in corporate bonds, gold and volatility-related assets in periods of market turmoil. Furthermore, we have shown that extremely bearish and bullish movements in those assets for which the EUA acts as a safe haven induce excess volatility in carbon markets, higher carbon trading volume and larger than normal EUA bid-ask spreads. These findings support the idea that some traders, by considering carb…
Urban segregation and unemployment: A case study of the urban area of Marseille – Aix-en-Provence (France)
2018
International audience; In this paper, we study the effects of the spatial organization of the urban area of Marseille – Aix-en-Provence on unemployment there. More specifically, differences in the characteristics of the residential population induce urban stratification with the result that urban structure may affect the probability of employment. In order to evaluate the effects of spatial structure on unemployment, we implement a spatial probit model to reveal the employment probabilities of young adults still living with their parents. Our results support the hypothesis that living in or near a deprived neighborhood decreases the probability of employment.
Quantile regression via iterative least squares computations
2012
We present an estimating framework for quantile regression where the usual L 1-norm objective function is replaced by its smooth parametric approximation. An exact path-following algorithm is derived, leading to the well-known ‘basic’ solutions interpolating exactly a number of observations equal to the number of parameters being estimated. We discuss briefly possible practical implications of the proposed approach, such as early stopping for large data sets, confidence intervals, and additional topics for future research.
Design-based estimation for geometric quantiles with application to outlier detection
2010
Geometric quantiles are investigated using data collected from a complex survey. Geometric quantiles are an extension of univariate quantiles in a multivariate set-up that uses the geometry of multivariate data clouds. A very important application of geometric quantiles is the detection of outliers in multivariate data by means of quantile contours. A design-based estimator of geometric quantiles is constructed and used to compute quantile contours in order to detect outliers in both multivariate data and survey sampling set-ups. An algorithm for computing geometric quantile estimates is also developed. Under broad assumptions, the asymptotic variance of the quantile estimator is derived an…
Productivity, Ownership and National Chains: Evidence from the British Retail Sector
2009
Abstract This paper investigates factors explaining firms' productivity differences in the British retail sector. In particular, using simultaneous quantile regressions, it aims to uncover performance gaps stemming from foreign ownership and multinationality, as well as national scale economies. The findings suggest that foreign ownership weakly explains differences in performance across retailers. Only when firms in the upper quantiles of the TFP distribution are compared, the role of foreign ownership gains statistical significance, although with exceptions. In addition, firms able to expand their infrastructure across Great Britain possess a productivity advantage over more local retaile…