|
on Financial Development and Growth |
| By: | Joao Sousa Andrade; Irina Syssoyeva-Masson |
| Abstract: | The relationship between public debt (d) and economic growth (g) has been and continue to be the subject of much empirical and theoretical attention in the literature as witnessing by the number of a growing empirical literature and very recent contributions. The policy recommendations of these studies have a great importance for governments and voters.However, the preliminary statistical data analyses are quite often absent from these studies what may in fact invalidate the empirical results. Therefore, the main purpose of this paper is to investigate the statistical properties of d (Debt-to- GDP) series to reveal the existence of long memory in d series besides the fact that this variable is not stationary and to shed light on importance of preliminary statistical data investigations. To do so we apply several statistical methods to the new data set on Gross Government Debt-to- GDP ratios for 87 countries over long period from the historical public debt database (HPDD) built by the International Monetary Fund (IMF). The main conclusions of this study are that d series has a long memory and should not be considered as a short-run phenomena, instead, its behavior should be analyzed in a long-term context; and its non-stationarity doesn't allow researchers to apply stationary econometrics methods to model its behavior. Thess finding implies that the relation between economic growth (g) and national debt (d), g = F (d), that has been characterizing the literature on the subject has not solid econometric foundations. After the review of the literature we propose to analyse the public debt ratio long memory and by the study of its stationary characteristics to reject the presence of cointegration between it and growth. The appropriate tests are employed. Absence of cointegration and rejection of the already traditional threshold effect of public debt on growth. The type of relation must respect econometric principles to avoid spurious relations. |
| Keywords: | For the larger sample: 87 countries., Finance, Growth |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9627&r=fdg |
| By: | Belke, Ansgar H. (University of Duisburg-Essen); Dreger, Christian (DIW Berlin); Dubova, Irina (Ruhr Graduate School in Economics) |
| Abstract: | The financial crisis led to a deep recession in many industrial countries. While large emerging countries recovered relatively quickly from the financial crisis, their performance deteriorated in the recent years, despite the modest recovery in advanced economies. The higher divergence of business cycles is closely linked to the Chinese transformation. During the crisis, the Chinese fiscal stimulus prevented a decline in GDP growth not only in that country, but also in resource-rich economies. The Chinese shift to consumption-driven growth led to a decline in commodity demand, and the environment became more challenging for many emerging markets. This view is supported by Bayesian VARs specified for the BRIC (Brazil, Russia, India, and China) countries. The results reveal a strong impact of international variables on GDP growth. In contrast to the other countries, China plays a crucial role in determining global trade and oil prices. Hence, the change in the Chinese growth strategy puts additional reform pressure on countries with abundant natural resources. |
| Keywords: | business cycle divergence, Chinese transformation, Bayesian VARs |
| JEL: | F44 E32 C32 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp10634&r=fdg |
| By: | Elena Deryugina (Bank of Russia, Russian Federation); Alexey Ponomarenko (Bank of Russia, Russian Federation) |
| Abstract: | We test the ability of early warning indicators that appear in the literature to predict credit cycle peaks in a cross-section of emerging markets. Our results confirm that the standard credit gap indicator performs satisfactorily. The robustness of real-time credit cycle determination may potentially (and with a risk of overfitting the data) be improved by simultane-ously monitoring GDP growth, banks’ non-core liabilities, the financial sector’s value added and (to a lesser extent) the change in the debt service ratio. |
| Keywords: | credit cycle, countercyclical capital buffers, early warning indicators, emerging markets. |
| JEL: | E37 E44 E51 |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:bkr:wpaper:wps17&r=fdg |