Econometrics最新文献_第10页

GDP and TFP in Poviats of the Łódzkie Voivodeship. Estimation and Analysis of Differentiation Łódzkie省各省的国内生产总值和全要素生产率。微分估计与分析

IF 1.5

Econometrics Pub Date : 2022-03-01 DOI: 10.15611/eada.2022.1.02

B. Dańska-Borsiak

{"title":"GDP and TFP in Poviats of the Łódzkie Voivodeship. Estimation and Analysis of Differentiation","authors":"B. Dańska-Borsiak","doi":"10.15611/eada.2022.1.02","DOIUrl":"https://doi.org/10.15611/eada.2022.1.02","url":null,"abstract":"Abstract The main objective of the research was to estimate the level of GDP and total factor productivity (TFP) in the counties (‘poviats’) of the Łódzkie voivodeship in the period 2002-2019. The gross product in poviats was determined by disaggregating the GDP of the Łódzkie voivodeship in proportion to the revenues of poviat budgets from personal income tax PIT and to the shares of poviats in the voivodeship wage fund. TFP was determined on the basis of a labour productivity model derived from the Cobb-Douglas production function with the assumption of constant returns to scale. A spatial panel data model estimated by the maximum likelihood method was applied. The poviat of Łódź was identified as the upper outlier in terms of the level of gross product. The dynamics of poviat values of GDP was similar to the national one, but poviats with a much faster rate of growth were identified. The highest level of TFP was observed in the poviat of Łódź. Very high productivity was also characteristic for the two other cities with poviat status, especially Skierniewice. In the Łódzkie voivodeship there was a progressive polarisation in terms of TFP with two leading poviats. No spillover processes were found. The capital city of the voivodeship, being itself the upper outlier, therefore did not play the role of a growth centre. It was also found that a clearly defined profile of economic activity in the poviat is conducive to faster TFP growth.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":"26 1","pages":"14 - 30"},"PeriodicalIF":1.5,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43320164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Single Functional Index Quantile Regression for Independent Functional Data Under Right-Censoring 右删截条件下独立函数数据的单函数指数分位数回归

IF 1.5

Econometrics Pub Date : 2022-03-01 DOI: 10.15611/eada.2022.1.03

Mohamed Mehdi Hamri, Sanaà Dounya Mekki, A. Rabhi, Nadia Kadiri

引用次数: 0

Identification in Parametric Models: The Minimum Hellinger Distance Criterion 参数模型中的辨识：最小Hellinger距离准则

IF 1.5

Econometrics Pub Date : 2022-02-21 DOI: 10.3390/econometrics10010010

David H. Pacini

引用次数: 2

Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models 基于分数驱动的冰河时代模型对气候变化的稳健估计和预测

IF 1.5

Econometrics Pub Date : 2022-02-16 DOI: 10.3390/econometrics10010009

Szabolcs Blazsek, A. Escribano

{"title":"Robust Estimation and Forecasting of Climate Change Using Score-Driven Ice-Age Models","authors":"Szabolcs Blazsek, A. Escribano","doi":"10.3390/econometrics10010009","DOIUrl":"https://doi.org/10.3390/econometrics10010009","url":null,"abstract":"We use data on the following climate variables for the period of the last 798 thousand years: global ice volume (Icet), atmospheric carbon dioxide level (CO2,t), and Antarctic land surface temperature (Tempt). Those variables are cyclical and are driven by the following strongly exogenous orbital variables: eccentricity of the Earth’s orbit, obliquity, and precession of the equinox. We introduce score-driven ice-age models which use robust filters of the conditional mean and variance, generalizing the updating mechanism and solving the misspecification of a recent climate–econometric model (benchmark ice-age model). The score-driven models control for omitted exogenous variables and extreme events, using more general dynamic structures and heteroskedasticity. We find that the score-driven models improve the performance of the benchmark ice-age model. We provide out-of-sample forecasts of the climate variables for the last 100 thousand years. We show that during the last 10–15 thousand years of the forecasting period, for which humanity influenced the Earth’s climate, (i) the forecasts of Icet are above the observed Icet, (ii) the forecasts of CO2,t level are below the observed CO2,t, and (iii) the forecasts of Tempt are below the observed Tempt. The forecasts for the benchmark ice-age model are reinforced by the score-driven models.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43903497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

The Impact of COVID-19 on Airfares—A Machine Learning Counterfactual Analysis COVID-19对机票的影响——机器学习反事实分析

IF 1.5

Econometrics Pub Date : 2022-02-16 DOI: 10.3390/econometrics10010008

Florian Wozny

引用次数: 1

Acknowledgment to Reviewers of Econometrics in 2021 对2021年计量经济学评论家的致谢

IF 1.5

Econometrics Pub Date : 2022-01-31 DOI: 10.3390/econometrics10010007

引用次数: 0

A New Estimator for Standard Errors with Few Unbalanced Clusters 一种具有少量不平衡簇的标准误差估计方法

IF 1.5

Econometrics Pub Date : 2022-01-21 DOI: 10.3390/econometrics10010006

Gianmaria Niccodemi, T. Wansbeek

{"title":"A New Estimator for Standard Errors with Few Unbalanced Clusters","authors":"Gianmaria Niccodemi, T. Wansbeek","doi":"10.3390/econometrics10010006","DOIUrl":"https://doi.org/10.3390/econometrics10010006","url":null,"abstract":"In linear regression analysis, the estimator of the variance of the estimator of the regression coefficients should take into account the clustered nature of the data, if present, since using the standard textbook formula will in that case lead to a severe downward bias in the standard errors. This idea of a cluster-robust variance estimator (CRVE) generalizes to clusters the classical heteroskedasticity-robust estimator. Its justification is asymptotic in the number of clusters. Although an improvement, a considerable bias could remain when the number of clusters is low, the more so when regressors are correlated within cluster. In order to address these issues, two improved methods were proposed; one method, which we call CR2VE, was based on biased reduced linearization, while the other, CR3VE, can be seen as a jackknife estimator. The latter is unbiased under very strict conditions, in particular equal cluster size. To relax this condition, we introduce in this paper CR3VE-λ, a generalization of CR3VE where the cluster size is allowed to vary freely between clusters. We illustrate the performance of CR3VE-λ through simulations and we show that, especially when cluster sizes vary widely, it can outperform the other commonly used estimators.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44726589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Entropy-Based Approach for Nonparametrically Testing Simple Probability Distribution Hypotheses 基于熵的简单概率分布假设非参数检验方法

IF 1.5

Econometrics Pub Date : 2022-01-14 DOI: 10.3390/econometrics10010005

R. Mittelhammer, G. Judge, Miguel Henry

{"title":"An Entropy-Based Approach for Nonparametrically Testing Simple Probability Distribution Hypotheses","authors":"R. Mittelhammer, G. Judge, Miguel Henry","doi":"10.3390/econometrics10010005","DOIUrl":"https://doi.org/10.3390/econometrics10010005","url":null,"abstract":"In this paper, we introduce a flexible and widely applicable nonparametric entropy-based testing procedure that can be used to assess the validity of simple hypotheses about a specific parametric population distribution. The testing methodology relies on the characteristic function of the population probability distribution being tested and is attractive in that, regardless of the null hypothesis being tested, it provides a unified framework for conducting such tests. The testing procedure is also computationally tractable and relatively straightforward to implement. In contrast to some alternative test statistics, the proposed entropy test is free from user-specified kernel and bandwidth choices, idiosyncratic and complex regularity conditions, and/or choices of evaluation grids. Several simulation exercises were performed to document the empirical performance of our proposed test, including a regression example that is illustrative of how, in some contexts, the approach can be applied to composite hypothesis-testing situations via data transformations. Overall, the testing procedure exhibits notable promise, exhibiting appreciable increasing power as sample size increases for a number of alternative distributions when contrasted with hypothesized null distributions. Possible general extensions of the approach to composite hypothesis-testing contexts, and directions for future work are also discussed.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48765194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Age–Period–Cohort Problem in Hedonic House Prices Models Hedonic房价模型中的年龄-时期-队列问题

IF 1.5

Econometrics Pub Date : 2022-01-10 DOI: 10.3390/econometrics10010004

Chung Yim Edward Yiu, K. Cheung

{"title":"The Age–Period–Cohort Problem in Hedonic House Prices Models","authors":"Chung Yim Edward Yiu, K. Cheung","doi":"10.3390/econometrics10010004","DOIUrl":"https://doi.org/10.3390/econometrics10010004","url":null,"abstract":"The age–period–cohort problem has been studied for decades but without resolution. There have been many suggested solutions to make the three effects estimable, but these solutions mostly exploit non-linear specifications. Yet, these approaches may suffer from misspecification or omitted variable bias. This paper is a practical-oriented study with an aim to empirically disentangle age–period–cohort effects by providing external information on the actual depreciation of housing structure rather than taking age as a proxy. It is based on appraisals of the improvement values of properties in New Zealand to estimate the age-depreciation effect. This research method provides a novel means of solving the identification problem of the age, period, and cohort trilemma. Based on about half a million housing transactions from 1990 to 2019 in the Auckland Region of New Zealand, the results show that traditional hedonic prices models using age and time dummy variables can result, ceteris paribus, in unreasonable positive depreciation rates. The use of the improvement values model can help improve the accuracy of home value assessment and reduce estimation biases. This method also has important practical implications for property valuations.","PeriodicalId":11499,"journal":{"name":"Econometrics","volume":" ","pages":""},"PeriodicalIF":1.5,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42417327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Forecasting Real GDP Growth for Africa 预测非洲实际GDP增长

IF 1.5

Econometrics Pub Date : 2022-01-06 DOI: 10.3390/econometrics10010003

Philip Hans Franses, Max Welz

引用次数: 0