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2021. vol. 25. No. 2
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177–195
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There are many different models for estimation of a yield curve from bond market quotes. These models are well suited for developed markets with high liquidity level and market data readily available. However, this is not always the case for developing markets that are characterized by infrequent trading, heterogeneous liquidity and frequent missing data. In this article we provide a review of the existing and theoretically possible solutions to the problems arising in the process of yield curve construction in developing markets. Our review shows, that all these problems can be effectively tackled by adapting traditional yield curves models to the observer liquidity level of developing market. Heterogeneous liquidity can be addressed by introducing liquidity-based weights into a yield curve model and by removing observations with atypical liquidity from the dataset. To solve missing data problem, we suggest using dynamic yield curve models or recreating missing observations with help of a supplementary model. In special cases when there are not enough bond issues on the market one is recommended to simplify yield curve model and use the data from other markets (e.g. derivative market). The article might be of a great use for market practitioners who operate on developing bond markets as well as for quants who are engaged in construction of yield curves. It also serves as a starting point for a further academic research in the area of term structure modelling in illiquid bond markets. |
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196–226
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Monetary financing of huge spending aimed to fight the pandemic had taken place under the unique and extremal circumstances. However, it also has long-term implications due largely to the accelerated increases in the value of financial assets. A simple model is proposed to study the complex and prolong process of normalizing money and finance. The latter is viewed as restructuring of the macro-financial portfolio of assets, which is subject to the stochastic dynamic of broad money. Such a model is focused on one of the most important macro-financial relationships: the optimal amount of liquidity must be adequately collateralized by the value of real wealth. If this condition is realized then an effective financial system could be formed. The provision of loans in such a system is secured and revenues of a risk-free asset portfolio are ade quate to repay all liabilities outstanding. In the short term, the riskless rate of return is similar to the rate of a macro-financial repo transaction. In the long run, the risk-free rate of return correspondence to a «neutral» interest rate has to be justified by the zero covariance of returns with the stochastic discount factor. Large deviations from the optimum of money, by disrupting the best configuration of assets and liabilities, cause undesirable consequences: either an illiquidity crisis or the credit expansion ending in a complete breakdown of the financial system. |
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227–262
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In this work we build a Bayesian vector autoregression model to estimate the impact of global economic activity shocks, supply shocks in the global oil market, as well as speculative oil shocks on key macroeconomic variables of the Russian economy: GDP, household consumption, fixed capital investment, import, export, real effective exchange rate, real wages and income, MIACR interest rate and GDP deflator. The model uses real oil prices, the index of global economic activity, oil production and oil inventories as exogenous variables. The model parameters are estimated for the period from Q1 1999 to Q4 2019. The dynamics of four exogenous variables is described using a separate external vector autoregression model, which is estimated over an extended time period from Q1 1974 to Q4 2019 in order to more accurately estimateits parameters and identify shocks. Shocks are identified based on the approach proposed in [Kilian, Murphy, 2014], which uses sign restrictions and restrictions on the price elasticities of oil demand and oil supply. According to estimates of impulse responses, such variables as real household consumption, imports, and the exchange rate respond positively and statistically significantly to all three shocks leading to an increase in oil prices. However, a shock to global economic activity has a stronger impact. With an increase in oil prices for real GDP, investment and exports a stable and statistically significant positive impact is observed only when this price increase is due to a shock to global economic activity. The work also estimates a forecast error variance decomposition and a historical decomposition of the domestic variables by shocks, which indicate the prevailing role of shocks in global economics activity in the dynamics of Russian macroeconomic variables. |
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263–291
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The choice of entrepreneurial activity and self-employment is associated with higher level of risk and requires a degree of love for it. The literature on risk preferences and entrepreneurship is extensive, but there is a limited amount of empirical research are on the crossroads of these topics. The papers focused on the Russian labor market taking into account not only the number of entrepreneurs, but also their quality and motivation of their choose, do not exist. Based on the data of the RLMS of the Higher School of Economics for 2016–2018, we build multi nomial logit models for choosing entrepreneurial activity and analyze the effect of risk preferences on this choice. The main conclusion of the work is that risk preferences are positively and not linearly correlated with the choice of entrepreneurial activity. The robustness of this result was tested by using different samples and different definitions of risk attitude and entrepreneurship. The conclusion is stable only for groups of voluntary entrepreneurs, however for involuntary ones the decision to be an entrepreneur does not correlate significantly with subjective attitude towards risk. Profiles of probability of entrepreneurship are more stable and ascending for men, but not for women, but this may be due to limited amount of observations of both groups . |
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292–308
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Currently, several similar but not identical statistical indicators characterizing the income of the population/households in Russia are published and all of these indicators are more or less official. Namely these are the following indicators: (a) an indicator of the real disposable monetary income of the population, published in all major statistical datasets, usually in the form of corresponding indices and officially used by government agencies;(b) an indicator of gross disposable income of households published in the official statistical yearbook «National accounts of Russia» as an absolute value at current prices; (c) an indicator of real disposable household income published in form of index in the statistical yearbook of the international organization (OECD) based on data for Russia received from Rosstat. The difference between them is that one of them focuses only on monetary incomes, while the other two use the classical interpretation of disposable income used in the system of national accounts, which also includes incomes in kind. There are also differences in approaches to deflation. But, objectively, the simultaneous use of all of these indicators is not so much due to the difference in their content or methodology, but rather to the peculiarities of the organization of the statistical system and the incomplete implementation of the system of national accounts in Russia. However, the simultaneous use of several indicators that are similar in terms of content leads to some confusion among users who do not have special statistical qualifications. The article examines the methodological differences between the indicators listed above, which lead to differences in their size and semantic content, as well as differences in the formats of their publication, and also provides recommendations for their correct use and interpretation. |
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309–346
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This paper investigates the increased role of extractive industry, particularly oil and gas, within the Dutch disease model between 2000–2018 in the Azerbaijan economy. Dutch disease phenomenon befalls when the national economy produces and exports a single commodity or a particular sector becomes the booming sector. Increased exports of particular goods and spendings of the accumulated mineral revenue appreciate the national currency, decreasing the competitiveness and thus the production or export volume of the non-booming sectors. Azerbaijan is an oil and gas-rich country which naturally actualizes the existence of Dutch disease syndrome . Therefore, the purpose of this research is to separately reveal the Dutch disease effects of resource movement and spending effects based on the theoretical frame work constructed from the core theory. The paper contains a comprehensive literature review and overall macroeconomic screening of the Azerbaijan economy to describe the preconditions of Dutch disease. Then, the study employs 42 multivariate linear ordinary least squares (OLS) estimations. The estimated models illustrate the presence of indirect de-industrialization (one form of resource movement effect) and the spending effect of the Dutch disease hypothesis. However, the paper does not find a direct negative influence of booming sectors on aggregated lagging (i.e., manufacturing and agriculture) and non-tradable sectors (services). Moreover, variables such as oil price growth rates, real effective exchange rate (REER), nominal effective exchange rate (NEER), and economic crisis periods failed to significantly explain the employment and real wages dynamics. However, these variables described certain influence channels in output and returns on capital growth rates. This paper sheds light on the interconnections between the Azerbaijan economy’s labor resources, government spending, and monetary channels. These interconnections indicate that the Dutch disease hypothesis holds true for Azerbaijan. Of the estimated OLS coefficients, 90.5% were highly stable, which suggests that the results are reliable. This study mainly tests the general theoretical expectations of the original Dutch disease model and presents a common ground to conceptualize the possible harmful effects of the booming oil and gas sectors in Azerbaijan. Any causal derivations should be handled carefully. |
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