Search results

1 – 10 of over 13000
Book part
Publication date: 18 January 2022

Andrew B. Martinez, Jennifer L. Castle and David F. Hendry

We investigate whether smooth robust methods for forecasting can help mitigate pronounced and persistent failure across multiple forecast horizons. We demonstrate that naive…

Abstract

We investigate whether smooth robust methods for forecasting can help mitigate pronounced and persistent failure across multiple forecast horizons. We demonstrate that naive predictors are interpretable as local estimators of the long-run relationship with the advantage of adapting quickly after a break, but at a cost of additional forecast error variance. Smoothing over naive estimates helps retain these advantages while reducing the costs, especially for longer forecast horizons. We derive the performance of these predictors after a location shift, and confirm the results using simulations. We apply smooth methods to forecasts of UK productivity and US 10-year Treasury yields and show that they can dramatically reduce persistent forecast failure exhibited by forecasts from macroeconomic models and professional forecasters.

Details

Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling
Type: Book
ISBN: 978-1-80262-062-7

Keywords

Book part
Publication date: 23 November 2020

Carolina Castagnetti, Luisa Rosti and Marina Töpfer

This paper analyzes the age pay gap in Italy (22%), particularly as it is of interest in an aging society and as it may affect social cohesion. Instead of the traditional approach…

Abstract

This paper analyzes the age pay gap in Italy (22%), particularly as it is of interest in an aging society and as it may affect social cohesion. Instead of the traditional approach for model selection, we use a machine-learning approach (post double robust Least Absolute Shrinkage Operator [LASSO]). This approach allows us to reduce Omitted Variable Bias (OVB), given data restrictions, and to obtain a robust estimate of the conditional age pay gap. We then decompose the conditional gap and analyze the impact of four further potential sources of heterogeneity (workers', sectors', and occupations' permanent heterogeneity as well as sample selection bias). The results suggest that age discrimination in pay is only perceived but not real in Italy for both men and women.

Details

Change at Home, in the Labor Market, and On the Job
Type: Book
ISBN: 978-1-83909-933-5

Keywords

Article
Publication date: 8 February 2021

Zhifeng Wang, Chi Zuo and Chunyan Zeng

Recently, the double joint photographic experts group (JPEG) compression detection tasks have been paid much more attention in the field of Web image forensics. Although there are…

Abstract

Purpose

Recently, the double joint photographic experts group (JPEG) compression detection tasks have been paid much more attention in the field of Web image forensics. Although there are several useful methods proposed for double JPEG compression detection when the quantization matrices are different in the primary and secondary compression processes, it is still a difficult problem when the quantization matrices are the same. Moreover, those methods for the different or the same quantization matrices are implemented in independent ways. The paper aims to build a new unified framework for detecting the doubly JPEG compression.

Design/methodology/approach

First, the Y channel of JPEG images is cut into 8 × 8 nonoverlapping blocks, and two groups of features that characterize the artifacts caused by doubly JPEG compression with the same and the different quantization matrices are extracted on those blocks. Then, the Riemannian manifold learning is applied for dimensionality reduction while preserving the local intrinsic structure of the features. Finally, a deep stack autoencoder network with seven layers is designed to detect the doubly JPEG compression.

Findings

Experimental results with different quality factors have shown that the proposed approach performs much better than the state-of-the-art approaches.

Practical implications

To verify the integrity and authenticity of Web images, the research of double JPEG compression detection is increasingly paid more attentions.

Originality/value

This paper aims to propose a unified framework to detect the double JPEG compression in the scenario whether the quantization matrix is different or not, which means this approach can be applied in more practical Web forensics tasks.

Details

International Journal of Web Information Systems, vol. 17 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 11 September 2017

Francesco Caracciolo and Marilena Furno

Several approaches have been proposed to evaluate treatment effect, relying on matching methods propensity score, quantile regression, influence function, bootstrap and various…

Abstract

Purpose

Several approaches have been proposed to evaluate treatment effect, relying on matching methods propensity score, quantile regression, influence function, bootstrap and various combinations of the above. This paper considers two of these approaches to define the quantile double robust (DR) estimator: the inverse propensity score weights, to compare potential output of treated and untreated groups; the Machado and Mata quantile decomposition approach to compute the unconditional quantiles within each group – treated and control. Two Monte Carlo studies and an empirical application for the Italian job labor market conclude the analysis. The paper aims to discuss these issue.

Design/methodology/approach

The DR estimator is extended to analyze the tails of the distribution comparing treated and untreated groups, thus defining the quantile based DR estimator. It allows us to measure the treatment effect along the entire outcome distribution. Such a detailed analysis uncovers the presence of heterogeneous impacts of the treatment along the outcome distribution. The computation of the treatment effect at the quantiles, points out variations in the impact of treatment along the outcome distributions. Indeed it is often the case that the impact in the tails sizably differs from the average treatment effect.

Findings

Two Monte Carlo studies show that away from average, the quantile DR estimator can be profitably implemented. In the real data example, the nationwide results are compared with the analysis at a regional level. While at the median and at the upper quartile the nationwide impact is similar to the regional impacts, at the first quartile – the lower incomes – the nationwide effect is close to the North-Center impact but undervalues the impact in the South.

Originality/value

The computation of the treatment effect at various quantiles allows to point out discrepancies between treatment and control along the entire outcome distributions. The discrepancy in the tails may differ from the divergence between the average values. Treatment can be more effective at the lower/higher quantiles. The simulations show the performance at the quartiles of quantile DR estimator. In a wage equation comparing long and short term contracts, this estimator shows the presence of an heterogeneous impact of short term contracts. Their impact changes depending on the income level, the outcome quantiles, and on the geographical region.

Details

Journal of Economic Studies, vol. 44 no. 4
Type: Research Article
ISSN: 0144-3585

Keywords

Open Access
Article
Publication date: 13 February 2024

Daniel de Abreu Pereira Uhr, Mikael Jhordan Lacerda Cordeiro and Júlia Gallego Ziero Uhr

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income…

Abstract

Purpose

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.

Design/methodology/approach

Municipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.

Findings

The findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.

Originality/value

This article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.

Details

EconomiA, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1517-7580

Keywords

Article
Publication date: 22 May 2023

Elena Kotyrlo

During the COVID-19 pandemic, transitory unemployment insurance (UI) policies substantially increased unemployment benefits (UBs) and the number of eligible groups in Russia. The…

Abstract

Purpose

During the COVID-19 pandemic, transitory unemployment insurance (UI) policies substantially increased unemployment benefits (UBs) and the number of eligible groups in Russia. The procedure for registering as unemployed was moved to an online platform. The present paper aims to distinguish the effect of anti-COVID-19 restrictions on unemployment from that of the transitory unemployment insurance policies.

Design/methodology/approach

Using 553,627 approved claims for unemployment benefits from the Russian Public Employment Service (PES) administrative records (June 2019–December 2020), monthly data on the number of individuals registered as unemployed are aggregated in a pseudo panel. A double-difference approach is employed to identify the effects of the social interaction intensity and teleworkability (TW) of the latest occupation on unemployment. The first is associated with a direct effect of anti-COVID-19 restrictions and the latter with the simplified application procedure.

Findings

The face-to-face (F2F) intensity of the latest occupation did not lead to any increase in the number of unemployed persons as could be expected in response to anti-COVID-19 restrictions. Job TW had two opposite effects on unemployment: it decreased individuals' risk of job loss and increased their likelihood of claiming unemployment benefits. Surprisingly, however, in line with the typical response of the Russian labour market to downturns, the latter dominated. The largest response was found among men and individuals with primary education.

Originality/value

This study is the first to attempt to distinguish the effect of anti-COVID-19 restrictions from that of the transitory UI policies on unemployment in Russia.

Details

Journal of Economic Studies, vol. 51 no. 1
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 10 June 2021

Asif Khan and Rachita Gulati

This paper aims to examine the total factor productivity (TFP) change and its components: efficiency change and technical change in microfinance institutions (MFIs) in India…

Abstract

Purpose

This paper aims to examine the total factor productivity (TFP) change and its components: efficiency change and technical change in microfinance institutions (MFIs) in India operating from 2005 to 2018. The study also scrutinizes the variations in productivity levels across the distinct organizational form and size groups of MFIs. In addition to this, the authors identify the contextual factors that determine TFP growth, catching-up and technology innovation in MFIs.

Design/methodology/approach

The study employs a smooth homogeneous bootstrap estimation procedure of Simar and Wilson (1999) for obtaining reliable estimates of Malmquist indices –productivity and its components – in a data envelopment analysis (DEA) framework for individual MFIs. In order to identify the determinants of productivity change and its components, the study follows Simar and Wilson's (2007) guidelines and applies a bootstrap truncated regression model. The double bootstrap procedure performs well, both in terms of allowing correct estimation of bias and deriving statistically consistent productivity estimates in the first and root mean square errors in the second stage of the analysis.

Findings

The empirical results reveal that the MFIs have shown average productivity growth of 6.70% during the entire study period. The observed productivity gains are primarily contributed by a larger efficiency increase at the rate of 4.80%, while technical progress occurs at 2.3%. Nonbanking financial companies (NBFC)-MFIs outperformed non-NBFC-MFIs. Small MFIs show the highest TFP growth in terms of size groups, followed by the large MFIs and medium MFIs. The bootstrap truncated regression results suggest that the credit portfolio, size and age of MFIs matter in achieving higher productivity levels.

Practical implications

The practical implication drawn from the study is that the Indian MFI industry might adopt the latest technology and innovations in the products, risk assessment and credit delivery to improve their productivity levels. The industry must focus on enhancing the managerial skill of its employees to achieve a high productivity level.

Originality/value

This study is perhaps the initial attempt to explain the productivity behavior of MFIs in India by deploying a statistically robust double bootstrap procedure in the DEA-based Malmquist Productivity Index (MPI) framework. The authors estimate the bias-adjusted productivity index and its decompositions, which represent more reliable and statistically consistent estimates. For contextual factors responsible for driving productivity change, the study deploys a bootstrap truncated regression approach.

Details

Benchmarking: An International Journal, vol. 29 no. 3
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 2 July 2021

Wenjue Zhu, Krishna P. Paudel, Sean Inoue and Biliang Luo

The purpose is to understand why contract instability occurs when small landowners lease their land to large landholders.

Abstract

Purpose

The purpose is to understand why contract instability occurs when small landowners lease their land to large landholders.

Design/methodology/approach

The authors develop a contract theoretical model to understand the stability problem in the farmland lease contract in China, where most landowners are small landholders.

Findings

Results from the doubly robust estimation method used on randomly selected interview data from 552 households in nine provinces of China indicate that contract instability can arise endogenously when large landholders sign a contract. The authors conclude that a suitable rent control regime or contract enforcement may be necessary to promote a large-scale farmland transfer in China.

Originality/value

The authors develop a contract theoretical model and apply it to the land rental market in China. Data used are original and collected from farmers located in nine provinces of China.

Details

China Agricultural Economic Review, vol. 13 no. 4
Type: Research Article
ISSN: 1756-137X

Keywords

Article
Publication date: 1 August 1998

Ò. À. Bèg, H.S. Takhar and V.M. Soundalgekar

Numerical results generated by a highly efficient finite‐difference method (originated by Keller for aerodynamical flows at the California Institute of Technology in 1970), and a…

Abstract

Numerical results generated by a highly efficient finite‐difference method (originated by Keller for aerodynamical flows at the California Institute of Technology in 1970), and a robust double shooting Runge‐Kutta‐Merson scheme are presented for the boundary layer equations representing the convection flow of a viscous incompressible fluid past a hot vertical flat plate embedded in a non‐Darcy porous medium. Viscous dissipation due to mechanical work is included in the temperature field equation. The computations for both solution techniques are compared at the leading edge (ξ = 0.0) and found to be in excellent agreement. The effects of the viscous heating parameter (Ec), thermal conductivity ratio (λ) and a Darcy porous parameter (Re/GrDa) on the fluid velocities, temperatures, local shear stress and wall heat transfer rate are discussed with applications to geothermal and industrial flows.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 8 no. 5
Type: Research Article
ISSN: 0961-5539

Keywords

Book part
Publication date: 13 March 2023

Omid Rafieian and Hema Yoganarasimhan

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy…

Abstract

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies – the Direct method, the Inverse Propensity Score (IPS) estimator, and the Doubly Robust (DR) method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research.

Details

Artificial Intelligence in Marketing
Type: Book
ISBN: 978-1-80262-875-3

Keywords

1 – 10 of over 13000