Epstein–Zin Utility, Asset Prices, and the Business Cycle Revisited

2019 ◽  
Vol 20 (4) ◽  
pp. e730-e758 ◽  
Author(s):  
Christopher Heiberger ◽  
Halvor Ruf
Keyword(s):  
Business Cycle ◽  
Capital Accumulation ◽  
Adjustment Costs ◽  
Building Blocks ◽  
Asset Markets ◽  
Dsge Models ◽  
Additional Degree ◽  
Dynamic Stochastic ◽  
The Business Cycle ◽  
Premium Puzzle

Abstract This paper discusses the advantages of Epstein and Zin (1989) (EZ) preferences when building dynamic stochastic general equilibrium (DSGE) models that are consistent with well-known stylized facts of both the business cycle and asset markets. To this end, we combine EZ preferences with several building blocks from the DSGE literature that has tried to solve the equity premium puzzle and to replicate characteristic statistics of the labor market. Our goal is to guide researchers in this area to useful modeling devices and to discuss EZ preferences vis-a-vis the standard time-additive expected utility function. EZ preferences separate the attitude toward risk from the attitude toward intertemporal substitution. We demonstrate that this additional degree of freedom allows us to closely match the empirical facts already in a frictionless production economy with endogenous labor supply. Our study follows Heer and Maußner (2013). We examine models that consider adjustment costs of capital accumulation, consumption habits, and frictions in the allocation of labor. Our empirical targets are estimated from German data.

scholarly journals The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Phuong V. Nguyen
Keyword(s):  
Business Cycle ◽  
Open Economy ◽  
Small Open Economy ◽  
Research Paper ◽  
New Keynesian ◽  
Dsge Model ◽  
Content Type ◽  
Business Cycle Fluctuations ◽  
Dynamic Stochastic ◽  
The Business Cycle

PurposeThe primary purpose of this paper is to investigate the sources of the business cycle fluctuations in Vietnam. To this end, the author develops a small open economy New Keynesian dynamic stochastic general equilibrium (SOE-NK-DSGE) model. Accordingly, this model includes various features, such as habit consumption, staggered price, price indexation, incomplete exchange-rate pass-through (ERPT), the failures of the law of one price (LOOP) and the uncovered interest rate parity. It is then estimated by using the Bayesian technique and Vietnamese data 1999Q1–2017Q1. Based on the estimated model, this paper analyzes the sources of the business cycle fluctuations in this emerging economy. Indeed, this research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.Design/methodology/approachA SOE-NK-DSGE model—Bayesian estimation.FindingsThis paper analyzes the sources of the business cycle fluctuations in Vietnam.Originality/valueThis research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.

scholarly journals Investment Dispersion and the Business Cycle

2014 ◽  
Vol 104 (4) ◽  
pp. 1392-1416 ◽  
Author(s):  
Rüdiger Bachmann ◽  
Christian Bayer
Keyword(s):  
Business Cycle ◽  
Adjustment Costs ◽  
Firm Risk ◽  
Firm Level ◽  
Cross Sectional ◽  
Capital Adjustment ◽  
Investment Rates ◽  
Business Cycle Model ◽  
The Business Cycle ◽  
Heterogeneous Firm

The cross-sectional dispersion of firm-level investment rates is procyclical. This makes investment rates different from productivity, output, and employment growth, which have countercyclical dispersions. A calibrated heterogeneous-firm business cycle model with nonconvex capital adjustment costs and countercyclical dispersion of firm-level productivity shocks replicates these facts and produces a correlation between investment dispersion and aggregate output of 0.53, close to 0.45 in the data. We find that small shocks to the dispersion of productivity, which in the model constitutes firm risk, suffice to generate the mildly procyclical investment dispersion in the data but do not produce serious business cycles. (JEL D42, D92, E32, G31, G32)

Anticipated Fiscal Policy Changes and Goods Market Adjustments

2006 ◽  
Vol 7 (2) ◽  
pp. 135-161 ◽  
Author(s):  
Stefan F. Schubert ◽  
Stephen J. Turnovsky
Keyword(s):  
Open Economy ◽  
Capital Accumulation ◽  
Government Expenditure ◽  
Small Open Economy ◽  
Adjustment Costs ◽  
Asset Markets ◽  
Policy Changes ◽  
Rates Of Return ◽  
Goods Market ◽  
Production Flexibility

Abstract Government policies are frequently known to be temporary and thus their termination is perfectly anticipated. These foreseen policy changes must be consistent with equilibrium in both the goods market and asset markets. Potential problems arise because prices often play dual roles, both as final goods prices, and as asset prices, as components of rates of return. We show how the economy accommodates an anticipated policy change depends upon its production flexibility and its structure. With flexible investment, an anticipated reduction in government expenditure is fully accommodated by capital accumulation. When investment involves adjustment costs, the marginal utility of wealth and the price of capital both jump so as to maintain equality among rates of return. Goods market clearance is maintained by a combination of increases in consumption and investment. Extensions of the model to include inventories and to a small open economy are also considered and contrasted.

scholarly journals Evolution of Modern Business Cycle Models: Accounting for the Great Recession

2018 ◽  
Vol 32 (3) ◽  
pp. 141-166 ◽  
Author(s):  
Patrick J. Kehoe ◽  
Virgiliu Midrigan ◽  
Elena Pastorino
Keyword(s):  
Business Cycle ◽  
Great Recession ◽  
The United States ◽  
Dsge Models ◽  
Real Business Cycle ◽  
Business Cycle Theory ◽  
The Great Recession ◽  
Modern Business ◽  
Dynamic Stochastic ◽  
The Rich

Modern business cycle theory focuses on the study of dynamic stochastic general equilibrium (DSGE) models that generate aggregate fluctuations similar to those experienced by actual economies. We discuss how these modern business cycle models have evolved across three generations, from their roots in the early real business cycle models of the late 1970s through the turmoil of the Great Recession four decades later. The first generation models were real (that is, without a monetary sector) business cycle models that primarily explored whether a small number of shocks, often one or two, could generate fluctuations similar to those observed in aggregate variables such as output, consumption, investment, and hours. These basic models disciplined their key parameters with micro evidence and were remarkably successful in matching these aggregate variables. A second generation of these models incorporated frictions such as sticky prices and wages; these models were primarily developed to be used in central banks for short-term forecasting purposes and for performing counterfactual policy experiments. A third generation of business cycle models incorporate the rich heterogeneity of patterns from the micro data. A defining characteristic of these models is not the heterogeneity among model agents they accommodate nor the micro-level evidence they rely on (although both are common), but rather the insistence that any new parameters or feature included be explicitly disciplined by direct evidence. We show how two versions of this latest generation of modern business cycle models, which are real business cycle models with frictions in labor and financial markets, can account, respectively, for the aggregate and the cross-regional fluctuations observed in the United States during the Great Recession.

scholarly journals Capital Buffer dan Faktor Penentunya di Indonesia

2020 ◽  
Vol 10 (2) ◽  
pp. 132
Author(s):  
Abel Tasman
Keyword(s):  
Business Cycle ◽  
Sample Selection ◽  
Adjustment Costs ◽  
Capital Adequacy ◽  
Bank Capital ◽  
Going Public ◽  
Capital Adequacy Ratio ◽  
Two Factors ◽  
The Difference ◽  
The Business Cycle

Capital buffer is defined as the difference between the bank's capital ratio and the capital adequacy ratio (Capital Adequacy Ratio) or CAR imposed by the Central Bank. Capital buffers can be used as capital reserves in times of various economic shocks so as to minimize risks faced by banks. A bank that has a high capital buffer reflects a high CAR as well, while a CAR that is too high is also not profitable for the bank, because this capital should be used for lending and investing in an effort to maximize profits. This study aims to determine the determinants of going public banking capital buffer in Indonesia for the period 2014 to 2018. The sample selection is based on purposive. Acting as the dependent variable is the capital buffer and the independent variables are ROE, NPL, Lag of capital buffer (〖BUFF〗 _ (t-1)), Size and GDP. This study used  multiple regression analysis. The results of this study indicate that the selected determinants of the capital buffer of going public banking in Indonesia are adjustment costs and the business cycle. Adjustment costs have a positive and significant effect on the capital buffer of going public banking in Indonesia and the business cycle has a negative and significant effect on the capital buffer of go public banking. public in Indonesia. Thus, the sample companies can optimize their capital buffer which can be ideal in order to maximize profits by considering the two factors above.

scholarly journals Output gap in the Czech economy: DSGE approach

2019 ◽  
Vol 19 (2) ◽  
pp. 137-156
Author(s):  
Jakub Bechný
Keyword(s):  
Business Cycle ◽  
General Equilibrium ◽  
Equilibrium Model ◽  
World Economy ◽  
Price Level ◽  
Dynamic Stochastic General Equilibrium ◽  
Domestic Demand ◽  
Output Gap ◽  
Dynamic Stochastic ◽  
The Business Cycle

Abstract This paper presents three measures of the output gap estimated by a dynamic stochastic general equilibrium model of the Czech economy. We argue that the most plausible description of the business cycle provides the output gap defined as a deviation from a flexible price level of output, which is generated solely by permanent growth shocks. Our model shows that 2006-2008 overheating of the economy and the following 2008-2009 slump can be largely attributed to development in a world economy and export and import sectors, while the 2012-2013 recession was caused mainly by a combination of adverse domestic demand and cost shocks.

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