http://www.bis.org/cbhub/list/jel_classification/jel_P27/index.rss Latest research hub papers with the JEL classification:P27 en http://www.suomenpankki.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/Documents/2012/dp1512.pdf Bank of Finland BOFIT Discussion Papers by Niko Korte Predictive power of confidence indicators for the Russian economy 2012-07-12T12:37:59Z This study examines the forecasting power of confidence indicators for the Russian economy. ARX models are fitted to the six confidence or composite indicators, which were then compared to a simple benchmark AR-model. The study used the output of the five main branches as the reference series. Empirical evidence suggests that confidence indicators do have forecasting power. The power is strongly influenced by the way which the indicator is constructed from the component series. The HSBC Purchasing Managers' Index (PMI), the OECD Composite Leading Indicator (CLI) and the OECD Business Confidence Indicator (BCI) were the best performers in terms of both the information criterion and forecasting accuracy. Predictive power of confidence indicators for the Russian economy 2012-07-12T12:37:59Z Abstract http://www.suomenpankki.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/Pages/dp1512.aspx Full text http://www.suomenpankki.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/Documents/2012/dp1512.pdf Niko Korte Niko Korte 2012-07-12 Bank of Finland BOFIT Discussion Papers E37 P27 http://www.bof.fi/NR/rdonlyres/3AF39502-5569-476A-B0FE-1A216A89F016/0/dp1107.pdf Bank of Finland BOFIT Discussion Papers by Aaron Mehrotra and Jouko Rautava Do sentiment indicators help to assess and predict actual developments of the Chinese economy? 2007-05-01T12:00:00Z This paper evaluates the usefulness of business sentiment indicators for forecasting developments in the Chinese real economy. We use data on diffusion indices collected by the People’s Bank of China for forecasting industrial production, retail sales and exports. Our bivariate vector autoregressive models, each composed of one diffusion index and one real sector variable, generally outperform univariate AR models in forecasting one to four quarters ahead. Similarly, principal components analysis, combining information from various diffusion indices, leads to enhanced forecasting performance. Our results indicate that Chinese business sentiment indicators convey useful information about current and future developments in the real economy. They also suggest that the official data provide a fairly accurate picture of the Chinese economy. Do sentiment indicators help to assess and predict actual developments of the Chinese economy? 2007-05-01T12:00:00Z Abstract http://www.bof.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/2007/dp1107.htm Full text http://www.bof.fi/NR/rdonlyres/3AF39502-5569-476A-B0FE-1A216A89F016/0/dp1107.pdf Jouko Rautava Aaron N. Mehrotra Aaron Mehrotra and Jouko Rautava 2007-04-26 Bank of Finland BOFIT Discussion Papers E32 E37 P27 http://www.bof.fi/NR/rdonlyres/033E8FAE-C55B-4B83-9132-62C81AA9D94C/0/dp1706.pdf Bank of Finland BOFIT Discussion Papers by Svetlana Ledyaeva and Mikael Linden Foreign direct investment and economic growth: Empirical evidence from Russian regions 2007-01-01T12:00:00Z Barro and Sala-I-Martin empirical framework of neoclassical Solow-Swan model is specified to determine the FDI impact on per capita growth in 74 Russian regions during period of 1996-2003. The Arellano-Bond GMM-DIFF methodology, developed for dynamic panel data models, is used in estimations. Results imply that in general FDI (or related investment components) do not contribute significantly to economic growth in Russia in the analyzed period. Regional growth in 1996-2003 is explained by the initial level of region’s economic development, the 1998 financial crisis, domestic investments, and exports. However some evidence of positive aggregate FDI effects in higher-income regions is relevant. Another interesting result is that natural resource availability seems to be growth-inducing in rich regions, while in poor regions it is not significant. We also found convergence between poor and rich regions in Russia. However FDI seems not to play any significant role in the recent growth convergence process among Russian regions. Foreign direct investment and economic growth: Empirical evidence from Russian regions 2007-01-01T12:00:00Z Abstract http://www.bof.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/2006/dp1706.htm Full text http://www.bof.fi/NR/rdonlyres/033E8FAE-C55B-4B83-9132-62C81AA9D94C/0/dp1706.pdf Mikael Linden Svetlana Ledyaeva Svetlana Ledyaeva and Mikael Linden 2006-12-14 Bank of Finland BOFIT Discussion Papers E22 F21 P27 http://www.bof.fi/NR/rdonlyres/59860936-C9C5-4B63-A340-714FD26D90F9/0/dp1105.pdf Bank of Finland BOFIT Discussion Papers by Bruno Merlevede, Koen Schoors On the Speed of Economic Reform: Tale of the Tortoise and the Hare 2005-09-01T12:00:00Z We analyse how the choice of reform speed and economic growth affect one another. We estimate a system of three equations where economic growth, economic reform and FDI are jointly determined. New reforms affect economic growth negatively, whereas the level of past reform leads to higher growth and attracts FDI. This means that the immediate adjustment cost of new reforms is counterbalanced by a future increase in FDI inflows and higher future growth through a higher level of past reform. Reform reversals contribute to lower growth. We use the model to simulate the impact of big bang reform and gradualist reform on economic growth. This is only meaningful in the presence of reform reversals, which requires aggregate uncertainty about the appropriate reform path. Using the coefficients from the empirical model, we find that even relatively small ex ante reversal probabilities suffice to tilt the balance in favour of gradualism. The case for gradualism gains strength if policymakers are short-sighted, but weakens if voters are myopic. Published in: Journal of Economic Policy Reform, Vol.10, No.1, 29-50, 2007. Print ISSN: 1384-1289. On the Speed of Economic Reform: Tale of the Tortoise and the Hare 2005-09-01T12:00:00Z Abstract http://www.bof.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/2005/dp1105.htm Full text http://www.bof.fi/NR/rdonlyres/59860936-C9C5-4B63-A340-714FD26D90F9/0/dp1105.pdf Koen Schoors Bruno Merlevede Bruno Merlevede, Koen Schoors 2005-08-15 Bank of Finland BOFIT Discussion Papers O57 P21 P26 P27 http://www.bof.fi/NR/rdonlyres/F76BA53F-E232-427C-9A03-5E71D76C1280/0/dp1004.pdf Bank of Finland BOFIT Discussion Papers by Yuko Kinoshita, Nauro F. Campos Estimating the Determinants of Foreign Direct Investment Inflows: How Important are Sampling and Omitted Variable Biases? 2004-09-01T12:00:00Z This paper investigates the importance of factor endowment vis-à -vis institutions in explaining the locational choice of foreign investors during the 1990s. Using dynamic panel estimation on data for transition economies, we find that low labour costs, bureaucratic efficiency (“institutions†), agglomeration economies and natural resource abundance are key factors explaining foreign investors’ decisions. However, sampling proves fundamental as these overall determinants mask deep and, so far empirically unexplored, differences between groups of recipient countries. For example, for the former Soviet Union economies we estimate that labour costs are no longer crucial, but abundance of natural resources and (interestingly) lower levels of human capital are. For Eastern Europe, we find that external liberalisation (one aspect of economic reform) is crucial in foreign investor’s decisions. The main message is that minimising sampling biases and accounting for previously omitted variables yields a different, much richer picture than previously available. Estimating the Determinants of Foreign Direct Investment Inflows: How Important are Sampling and Omitted Variable Biases? 2004-09-01T12:00:00Z Abstract http://www.bof.fi/bofit_en/tutkimus/tutkimusjulkaisut/dp/2004/dp1004.htm Full text http://www.bof.fi/NR/rdonlyres/F76BA53F-E232-427C-9A03-5E71D76C1280/0/dp1004.pdf Nauro F. Campos Yuko Kinoshita Yuko Kinoshita, Nauro F. Campos 2004-08-10 Bank of Finland BOFIT Discussion Papers C33 F21 O16 P27