Forecasting regional GDPs: a comparison with spatial dynamic panel data models

IF 1.5 3区经济学 Q2 ECONOMICS

Spatial Economic Analysis Pub Date : 2023-05-04 DOI:10.1080/17421772.2023.2199034

A. Billé, Alessio Tomelleri, F. Ravazzolo

{"title":"Forecasting regional GDPs: a comparison with spatial dynamic panel data models","authors":"A. Billé, Alessio Tomelleri, F. Ravazzolo","doi":"10.1080/17421772.2023.2199034","DOIUrl":null,"url":null,"abstract":"ABSTRACT The monitoring of the regional (provincial) economic situation is of particular importance due to the high level of heterogeneity and interdependences among different territories. Although econometric models allow for spatial and serial correlation of various kinds, the limited availability of territorial data restricts the set of relevant predictors at a more disaggregated level, especially for gross domestic product (GDP). Combining data from different sources at NUTS-3 level, this paper evaluates the predictive performance of a spatial dynamic panel data model with individual fixed effects and some relevant exogenous regressors, by using data on total gross value added (GVA) for 103 Italian provinces over the period 2000–2016. A comparison with nested panel sub-specifications as well as pure temporal autoregressive specifications has also been included. The main finding is that the spatial dynamic specification increases forecast accuracy more than its competitors throughout the out-of-sample, recognising an important role played by both space and time. However, when temporal cointegration is detected, the random-walk specification is still to be preferred in some cases even in the presence of short panels.","PeriodicalId":47008,"journal":{"name":"Spatial Economic Analysis","volume":"18 1","pages":"530 - 551"},"PeriodicalIF":1.5000,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spatial Economic Analysis","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1080/17421772.2023.2199034","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}

引用次数: 2

Abstract

ABSTRACT The monitoring of the regional (provincial) economic situation is of particular importance due to the high level of heterogeneity and interdependences among different territories. Although econometric models allow for spatial and serial correlation of various kinds, the limited availability of territorial data restricts the set of relevant predictors at a more disaggregated level, especially for gross domestic product (GDP). Combining data from different sources at NUTS-3 level, this paper evaluates the predictive performance of a spatial dynamic panel data model with individual fixed effects and some relevant exogenous regressors, by using data on total gross value added (GVA) for 103 Italian provinces over the period 2000–2016. A comparison with nested panel sub-specifications as well as pure temporal autoregressive specifications has also been included. The main finding is that the spatial dynamic specification increases forecast accuracy more than its competitors throughout the out-of-sample, recognising an important role played by both space and time. However, when temporal cointegration is detected, the random-walk specification is still to be preferred in some cases even in the presence of short panels.

查看原文本刊更多论文

预测区域GDP：与空间动态面板数据模型的比较

摘要由于不同地区之间高度的异质性和相互依存性，对地区（省）经济形势的监测尤为重要。尽管计量经济模型允许各种类型的空间和序列相关性，但领土数据的有限可用性限制了在更细分的层面上的相关预测因素集，尤其是国内生产总值。本文结合NUTS-3水平上不同来源的数据，通过使用意大利103个省2000-2016年期间的总增加值数据，评估了具有个体固定效应和一些相关外生回归的空间动态面板数据模型的预测性能。还包括与嵌套面板子规范以及纯时间自回归规范的比较。主要发现是，在整个样本外，空间动态规范比其竞争对手更能提高预测精度，认识到空间和时间都发挥着重要作用。然而，当检测到时间协整时，在某些情况下，即使在存在短面板的情况下，随机游走规范仍然是优选的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Spatial Economic Analysis ECONOMICS-

CiteScore

5.40

自引率

21.70%

发文量

期刊介绍： Spatial Economic Analysis is a pioneering economics journal dedicated to the development of theory and methods in spatial economics, published by two of the world"s leading learned societies in the analysis of spatial economics, the Regional Studies Association and the British and Irish Section of the Regional Science Association International. A spatial perspective has become increasingly relevant to our understanding of economic phenomena, both on the global scale and at the scale of cities and regions. The growth in international trade, the opening up of emerging markets, the restructuring of the world economy along regional lines, and overall strategic and political significance of globalization, have re-emphasised the importance of geographical analysis.