DSGE MODELING IN THE FOCUS OF FISCAL AND MONETARY ISSUES

Due to the intensification of the economic crisis in the late 20th – early 21st, fiscal and monetary issues have activated an impressive discourse, which became the prominent markers of helpful research engines for supporting sustainable development in the face of increasing debt burden. One of the most effective scenario modeling methods for implementing economic policy is the Dynamic Stochastic General Equilibrium (DSGE) model. The global practice in operating with such a tool is focused mainly on developed countries, while developing economies have significant differences and require notable adjustments. The goal of the presented study is to highlight the exercise of solving fiscal and monetary issues using a DSGE modeling toolkit for a developing economy. An incomplete list of proven features of DSGE modeling for a developing economy regarding the solution of fiscal and monetary issues includes: a high proportion of non-Ricardian consumers, forced unemployment, limited competition in the labor market, a significant volume of remittances, low efficiency and high capital return of public investment, low degree of home bias, smoothing crowding-out effect, financial repressions, limited mobility in the international capital market, lack of clear and transparent rules, and overruled fiscal and monetary spaces. In the context of the fiscal and monetary study, problematic issues of DSGE modeling are not limited only to the difficulties of theoretical and technical solutions. With the gradual elimination of barriers between the sectors in the world economy due to global transformations, the driving forces of growth require reviewing the anti-crisis management toolkit. Taking into account the progressive technological shifts in the field of information transmission and processing, the solution of the listed problematic issues related to the theoretical and technical support of DSGE modeling for a developing economy adds a new definition to the powerful hardware tool that reproduces specific scenario conditions for assessing the consequences of economic policy implementations.

The State of DSGE Modeling

Dynamic stochastic general equilibrium (DSGE) modeling can be structured around six key criticisms leveled at the approach. The first is fundamental and common to macroeconomics and microeconomics alike—namely, problems with rationality and expected utility maximization (EUM). The second is that DSGE models examine fluctuations about an exogenous balanced growth path and there is no role for endogenous growth. The third consists of a number of concerns associated with estimation. The fourth is another fundamental problem with any micro-founded macro-model—that of heterogeneity and aggregation. The fifth and sixth concern focus on the rudimentary nature of earlier models that lacked unemployment and a banking sector. A widely used and referenced example of DSGE modeling is the Smets-Wouters (SW) medium-sized NK model. The model features rational expectations and, in an environment of uncertainty, EUM by households and firms. Preferences are consistent with a nonstochastic exogenous balanced growth path about which the model is solved. The model can be estimated by a Bayesian systems estimation method that involves four types of representative agents (households, final goods producers, trade unions, and intermediate good producers). The latter two produce differentiated labor and goods, respectively, and, in each period of time, consist of a proportion locked into existing contracts and the rest that can reoptimize. There is underemployment but no unemployment. Finally, an arbitrage condition imposed on the return on capital and bonds rules out financial frictions. Thus the model, which has become the gold standard for DSGE macro-modeling, features all six areas of concern. The model can be used as a platform to examine how the current generation of DSGE models has developed in these six dimensions. This modeling framework has also used for macro-economic policy design.

Behavioral economics and DSGE-modeling

The article considers the “behavioral” modification of the standard DSGE model proposed by X. Gabaix. In his model, agents behave in a boundedly rational manner, showing incomplete attention to macroeconomic statistics. Moreover, unlike other attempts to abandon the hypothesis of rational expectations in favor of a model of adaptive and/or static expectations, the Gabaix model is initially constructed taking into account the inattention of economic agents to macro variables. The consequence of bounded rationality is that monetary policy is less effective (compared to the model of rational expectations) and, conversely, fiscal policy is effective due to the fact that Ricardo equivalence is not fulfilled. If the inertia of inflation expectations is taken into account in the Gabaix model, it demonstrates that the interest rate has a positive effect on inflation in the long run. Bayesian estimates for the rationality coefficient in the Russian economy are presented. Moreover, attention to inflation is much lower than attention to the variable of economic activity.

FINANCIAL INTEGRATION AND MACROECONOMIC VOLATILITY: NEW EVIDENCE FROM DSGE MODELING

This paper provides a brief overview of theoretical and empirical literature on financial integration and macroeconomic volatility nexus highlighting how the degree of financial integration affects the volatility of macroeconomic fundamentals. Using a dynamic stochastic general equilibrium (DSGE) model, our findings show that: (i) higher degree of financial integration tends to decrease short-run volatility; (ii) following monetary policy shocks, financial integration increases nominal exchange rate and output volatility and reduces both nominal and real interest rates and consumption volatility; and (iii) in response to fiscal shocks, financial integration stabilizes all variables under the assumption of perfect capital mobility.

Applications of DSGE Models in Central Banking: Key Issues Explored During Research Workshop of the National Bank of Ukraine

This paper reviews a research workshop that was held by the National Bank of Ukraine (NBU) in November 2018 on the application of DSGE models in central banking. We summarize the discussion of the advantages and drawbacks of DSGE modeling and potential ways to resolve issues and improve the models. Furthermore, this paper provides guidance on using DSGE models for forecasting and policy analysis.

Contrasting Visions for Macroeconomic Theory: DSGE and OEE

Dynamic stochastic general equilibrium (DSGE) modeling remains the workhorse of contemporary macroeconomics despite a growing number of critiques of its ability to explain the aggregate properties of an economic system. For the most part, those critiques accept the DSGE presumption that traditional macro data are primitive, causal data. This leads to a stipulative style of analysis where macro variables are explained in terms of one another. In contrast, we set forth an open-ended evolutionary (OEE) framework for an OEE macroeconomics. Within this framework, systems data are not primitive, but are derived from prior microlevel interactions without any presumption that those macrolevel derivations reflect systemic equilibrium among the microlevel primitive sources of action. We explore some contours of an OEE framework by placing coordination games within an ecological setting where there is no agent who has universal knowledge relevant to that ecology of games.JEL Classifications: B40, C73, D51, D85, E02

THE REGIME-DEPENDENT EVOLUTION OF CREDIBILITY: A FRESH LOOK AT HONG KONG'S LINKED EXCHANGE RATE SYSTEM

An estimated Markov-switching DSGE modeling framework that allows for parameter shifts across regimes is employed to test the hypothesis of regime-dependent credibility of Hong Kong's linked exchange rate system. The baseline model distinguishes two regimes with respect to the time-series properties of the risk premium. Regime-dependent impulse responses to macroeconomic shocks reveal substantial differences in spreads. To test the sensitivity of the results, a number of robustness checks are performed. The findings contribute to efforts at modeling exchange rate regime credibility as a nonlinear process with two distinct regimes.