Should Forecasters Use Real-time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence
Katja Heinisch, Rolf Scheufele
Abstract
In this paper we investigate whether differences exist among forecasts using real-time or latest-available data to predict gross domestic product (GDP). We employ mixed-frequency models and real-time data to reassess the role of survey data relative to industrial production and orders in Germany. Although we find evidence that forecast characteristics based on real-time and final data releases differ, we also observe minimal impacts on the relative forecasting performance of indicator models. However, when obtaining the optimal combination of soft and hard data, the use of final release data may understate the role of survey information.
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Alternatives to GDP - Measuring the Impact of Natural Disasters using Panel Data
Jörg Döpke, Philip Maschke
Journal of Economic and Social Measurement,
Nr. 3,
2016
Abstract
A frequent criticism of GDP states that events that obviously reduce welfare of people can nevertheless increase GDP per capita. We use data of natural disasters as quasi experiments to examine whether alternatives to GDP (Human Development Index, Progress Index, Index of Economic Well-Being and a Happiness Index) lead to more plausible responses to disasters. Applying a Differences-in-Differences approach and estimates from various panels of countries we find no noteworthy differences between the response of real GDP per capita and the responses of suggested alternative welfare measures to a natural disaster except for the Human Development Index.
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FDI, Human Capital and Income Convergence — Evidence for European Regions
Björn Jindra, Philipp Marek, Dominik Völlmecke
Economic Systems,
Nr. 2,
2016
Abstract
This study examines income convergence in regional GDP per capita for a sample of 269 regions within the European Union (EU) between 2003 and 2010. We use an endogenous broad capital model based on foreign direct investment (FDI) induced agglomeration economies and human capital. By applying a Markov chain approach to a new dataset that exploits micro-aggregated sub-national FDI statistics, the analysis provides insights into regional income growth dynamics within the EU. Our results indicate a weak process of overall income convergence across EU regions. This does not apply to the dynamics within Central and East European countries (CEECs), where we find indications of a poverty trap. In contrast to FDI, regional human capital seems to be associated with higher income levels. However, we identify a positive interaction of FDI and human capital in their relation with income growth dynamics.
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Multidimensional Well-being and Regional Disparities in Europe
Jörg Döpke, A. Knabe, Cornelia Lang, Philip Maschke
Abstract
Using data from the OECD Regional Well-Being Index – a set of quality-of-life indicators measured at the sub-national level, we construct a set of composite well-being indices. We analyse the extent to which the choice of five alternative aggregation methods affects the well-being ranking of regions. We find that regional inequality in these composite measures is lower than regional inequality in gross-domestic product (GDP) per capita. For most aggregation methods, the rank correlation across regions appears to be quite high. It is also shown that using alternative indicators instead of GDP per capita would only have a small effect on the set of regions eligible for aid from EU Structural Funds. The exception appears to be an aggregation based on how individual dimensions of welfare relate to average life satisfaction across regions, which would substantially change both the ranking of regions and which regions would receive EU funds.
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