This article primarily aims to estimate the impact of the Armenian revolution and test the hypothesis, that is, the benefits of revolution and establishment of democracy can be seen even in the first year after the political change. To calculate the short-term net surplus of the revolution, we estimated the difference between the projection of Armenian economic activity for the four quarters after the revolution, using only pre-revolutionary (assuming there was no revolution) and real data for the same period after the revolution. Using deep neural network models, such as recurrent neural networks and convolutional neural networks (CNN), we compared prediction accuracy with structural econometrics, such as autoregressive integrated moving average and error correction model, using pre-revolutionary data (2000Q1–2018Q1) for Armenia and combinations of models using an ensembling mechanism. As a result, CNN overperformed the rest of the models. The CNN simulation on post-revolutionary data indicates that during the period 2018-Q2–2019-Q1, Armenia gained approximately 850 million EUR in terms of GDP, thanks to the revolution and the new government. Moreover, out of seven models, the five best models in terms of accuracy indicated that the revolution had no negative impact on the Armenian economy, as the actual values were within or above the 95% confidence interval of the prediction.
The paper aims to find what determines the choice of companies listed on the Warsaw Stock Exchange (WSE) between public debt (corporate bonds) and private debt (bank loans). For this purpose, we estimate logistic regression models and panel models of corporate borrowing determinants to compare the impact of enterprise characteristics on financing with the use of corporate bonds or bank loans. In this study, we are interested in explanatory variables that explain the role of transparency measured by the level of information disclosure; and a risk proxy of the variability of operational cash flows and investment risk (retrieved from generalised auto-regressive conditional heteroscedasticity [GARCH] models estimated on companies’ stocks [shares] trading on the WSE).
This paper studies how macroprudential policy tools applied to the housing market can complement the interest rate-based monetary policy in achieving one additional stabilization objective, defined as keeping either economic activity or credit at some exogenous (and possibly time-varying) levels. We show analytically in a canonical New Keynesian model with housing and collateral constraints that using the loan-to-value (LTV) ratio, tax on credit or tax on property as additional policy instruments does not resolve the inflation-output volatility tradeoff. Perfect targeting of inflation and credit with monetary and macroprudential policy is possible only if the role of housing debt in the economy is sufficiently small. The identified limits to the considered policies are related to their predominantly intertemporal impact on decisions made by financially constrained agents, making them poor complements to monetary policy, which also operates at an intertemporal margin. These limits can be overcome if macroprudential policy is instead designed such that it sufficiently redistributes income between savers and borrowers.
This article presents the role of clusters in the Polish innovation system. This role has evolved in recent years due to maturing of cluster organisations and the expansion of their ability not just to provide services for cluster members but also to perform selected public tasks. This study aims to provide a better understanding of the nature and extent to which clusters can contribute to the objectives of development policies and thus to the economic development of the Polish economy and answer the question what role clusters can play in the innovation system. Based on a survey of 44 cluster organisations in Poland and interviews with cluster managers, the study explores the possibility of engaging Polish cluster organisations in the implementation of public policies. The results confirm that many of the Polish clusters achieved such a level of development that they themselves see the possibility of engaging in public tasks, for example education and specialised training, helping enterprises in digital transformation, monitoring technological trends, and so on. Therefore, it is justified pursuing a dual cluster policy. This duality means focus on two objectives: supporting cluster organisations on the one hand and implementing cluster-based development policies on the other hand.
This article focuses on the determinants of inward foreign direct investment (FDI) in Russia. The article briefly describes the historical context of foreign investment policymaking in Russia since the beginning of the economic transition to an open market economy after the dissolution of the Soviet Union. When compared to other developing countries, Russia's FDI stocks continue to lag despite a set of proactive measures undertaken by the national government. Following the literature review, the most commonly cited determinants explaining inward FDI in Russia include market size, labour productivity, trade and investment barriers, domestic exchange rate, rule of law and institutional framework.
This article aims to contribute empirically to the study of determinants of inward FDI in Russia.
This article uses the Pseudo-Poisson Maximum Likelihood (PPML) estimation technique, the robustness of the PPML estimation is then verified using a standard autoregressive integrated moving average (ARIMA) model with the Durbin–Watson autocorrelation test.
Our benchmark results suggest the efficiency-seeking motive of FDI over a market seeking and horizontal motive as a main reason for inward FDI in Russia. The ARIMA regression indicates the absence of statistical significance of economic openness and variables of labour productivity. Overall, the market size and tax rate variables have the most positive effects on the inward FDI, while barriers to trade and sanctions have the most negative effects. The results confirm that for transitional economies, integration into the world economy, proactive local development and tax cuts for outside investors remain to be critical when it comes to attracting FDI.