The Role of Wage Formation in Empirical Macroeconometric Models

2021 ◽  
Author(s):  
Ragnar Nymoen
Keyword(s):  
Common Ground ◽  
Phillips Curve ◽  
System Thinking ◽  
Equation Modeling ◽  
Nominal Wage ◽  
Dsge Models ◽  
Wage Setting ◽  
Wage Formation ◽  
Dynamic Stochastic ◽  
Equilibrium Correction

The specification of model equations for nominal wage setting has important implications for the properties of macroeconometric models and requires system thinking and multiple equation modeling. The main models classes are the Phillips curve model (PCM), the wage–price equilibrium correction model (WP-ECM), and the New Keynesian Phillips curve (NKPCM). The PCM was included in the macroeconometric models of the 1960s. The WP‑ECM arrived in the late 1980s. The NKPCM is central in dynamic stochastic general equilibrium models (DSGEs). The three model classes can be interpreted as different specifications of the system of stochastic difference equations that define the supply side of a medium-term macroeconometric model. This calls for an appraisal of the different wage models, in particular in relation to the concept of the non-accelerating inflation rate of unemployment (NAIRU, or natural rate of unemployment), and of the methods and research strategies used. The construction of macroeconomic model used to be based on the combination of theoretical and practical skills in economic modeling. Wage formation was viewed as being forged between the forces of markets and national institutions. In the age of DSGE models, macroeconomics has become more of a theoretical discipline. Nevertheless, producers of DSGE models make use of hybrid forms if an initial theoretical specification fails to meet a benchmark for acceptable data fit. A common ground therefore exists between the NKPC, WP‑ECM, and PCM, and it is feasible to compare the model types empirically.

scholarly journals HETEROGENEITY IN WAGE SETTING BEHAVIOR IN A NEW-KEYNESIAN MODEL

2019 ◽  
Vol 24 (6) ◽  
pp. 1512-1546
Author(s):  
Sylvester C. W. Eijffinger ◽  
Anderson Grajales-Olarte ◽  
Burak R. Uras
Keyword(s):  
New Keynesian ◽  
Wage Rigidity ◽  
Nominal Wage ◽  
Dsge Model ◽  
Wage Setting ◽  
Sticky Information ◽  
Bayesian Techniques ◽  
Us Economy ◽  
Output Fluctuations ◽  
Dynamic Stochastic

In this paper we estimate a New-Keynesian dynamic stochastic general equilibrium (NK DSGE) model with heterogeneity in price and wage setting behavior. In a recent study, Coibion and Gorodnichenko develop a DSGE model, in which firms follow four different types of price setting schemes: sticky prices, sticky information, rule-of-thumb, or flexible prices. We enrich Coibion and Gorodnichenko framework by incorporating heterogeneity in nominal wage setting behavior among households. We solve this DSGE model and estimate it using Bayesian techniques for the US economy from 1955 to 2008. The estimation results show the relevance of heterogeneity in wage setting among households. More importantly, we identify qualitative and quantitative business cycle features allowed by the heterogeneity in wage rigidity, such as the persistence in price and wage inflation, which a standard NK model with only Calvo-type wage rigidity fails to achieve. We also show that modeling wage-rigidity heterogeneity—as opposed to standard Calvo wages—amplifies the macroeconomic output fluctuations resulting from a technology shock while it mitigates the output fluctuations following a monetary tightening.

THE NEW KEYNESIAN WAGE PHILLIPS CURVE: CALVO VS. ROTEMBERG

2018 ◽  
Vol 24 (5) ◽  
pp. 1017-1041 ◽  
Author(s):  
Benjamin Born ◽  
Johannes Pfeifer
Keyword(s):  
Phillips Curve ◽  
New Keynesian ◽  
Adjustment Cost ◽  
Dsge Models ◽  
Fixed Costs ◽  
Wage Setting ◽  
First Order ◽  
Wide Range ◽  
Order Of Magnitude ◽  
Welfare Implications

We systematically evaluate how to translate a Calvo wage duration into an implied Rotemberg wage adjustment cost parameter in medium-scale New Keynesian DSGE models by making use of the well-known equivalence of the two setups at first order. We consider a wide range of felicity functions and show that the assumed household insurance scheme and the presence of labor taxation greatly matter for this mapping, giving rise to differences of up to one order of magnitude. Our results account for the inclusion of wage indexing, habit formation in consumption, and the presence of fixed costs in production. We also investigate the conditional and unconditional welfare implications of the wage-setting schemes under efficient and distorted steady states.

Essays on inflation dynamics, economic fluctuations and fiscal policy

2015 ◽  
Author(s):  
◽  
Kuo-Hsuan Chin
Keyword(s):  
Government Spending ◽  
Bayes Factor ◽  
Phillips Curve ◽  
Theoretical Models ◽  
New Keynesian ◽  
Dsge Models ◽  
Inflation Dynamics ◽  
Fiscal Stimulus ◽  
Short Run ◽  
Dynamic Stochastic

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Understand the short-run inflation dynamics is essential for conducting the fiscal or monetary policies, and the New Keynesian Phillips Curve (hereafter, NKPC) has been widely used for charactering it in the past two decades. The mixed results arise from estimating NKPC with constant parameters. I argue that the timevarying features of parameters in NKPC help reconcile the conflicting conclusions in the empirical NKPC studies. Moreover, it is useful for policymakers to estimate the effect of government spending on private spending and aggregate output. However, the precise estimate of such effects is hard to pin down since the researchers use very different theoretical models, ranging from a frictionless Real Business Cycle model to a medium-scale New Keynesian model with many nominal and real frictions. I take a top-down approach by generalizing the Dynamic Stochastic General Equilibrium (DSGE) model of Smets and Wouters (2007), in which many DSGE models can be viewed as simpler versions of it after removing certain nominal or real frictions. I take a Bayesian approach to estimate the fiscal stimulus in different models, which are obtained by imposing a tight prior on a single parameter or a combination of tight priors on multiple parameters. I pick up an appropriate model via Bayes factor and then use it to forecast the effect of government spending. I find a positive short-run effect but a negative long-run consequence of fiscal stimulus.

scholarly journals Development of the fundamentals of DSGE-modeling

2021 ◽  
Vol 2021 (01) ◽  
pp. 67-85
Author(s):  
Serhii Shvets` ◽  
◽  
Keyword(s):  
Structural Changes ◽  
Phillips Curve ◽  
Radical Change ◽  
New Keynesian ◽  
Dsge Models ◽  
Inflation Expectations ◽  
Macro Modeling ◽  
Theoretical Approaches ◽  
New Instrument ◽  
Dynamic Stochastic

This article attempts to analyze the evolution of approaches that constitute grounds for macro modeling. The counteraction to destructive consequences of crises assumes practical use of model apparatus as a necessary tool for preventing destabilization. The article aims to study the progressive stages and identify unsettled issues and promising ways to assist macro models' evolution. The fundamental Marshall's and Walras's platforms supported progressive changes following the destructive Great Depression and Great Inflation in the USA in 1920-1970 and marked a new trend in macro modeling called dynamic stochastic general equilibrium (DSGE) models. The new instrument is remarkable for a radical change in macro modeling approaches, where microeconomics comes to the fore. DSGE models debuted by invoking four essential ingredients: the Phillips curve, adaptive inflation expectations, anchoring nominal prices, and an endogenous production function. The progression stages of theoretical approaches to macro modeling incorporate the classical and Keynesian schools' advanced innovations. The evolution of macro modeling has five generations of models: Keynesian, classical, RBS, new Keynesian, and new Keynesian DSGE models. Among advantages of DSGE models are "political neutrality," distinguishing the shocks into economic and political ones, and establishing the upshots of significant structural changes in the economy. The next generation of macro models is called to solve four pressing issues: establishing financial frictions, relaxing rational expectations, introducing heterogeneous agents, and underpinning the framework with more appropriate microfoundations.

scholarly journals The Inflation-Output Trade-Off with Downward Wage Rigidities

2011 ◽  
Vol 101 (4) ◽  
pp. 1436-1466 ◽  
Author(s):  
Pierpaolo Benigno ◽  
Luca Antonio Ricci
Keyword(s):  
Phillips Curve ◽  
Closed Form Solution ◽  
Form Solution ◽  
Nominal Wage ◽  
Average Output ◽  
Macroeconomic Volatility ◽  
Long Run ◽  
Idiosyncratic Shocks ◽  
Dynamic Stochastic ◽  
Macroeconomic Implications

The macroeconomic implications of downward nominal wage rigidities are analyzed via a dynamic stochastic general equilibrium model featuring aggregate and idiosyncratic shocks. A closed-form solution for a long-run Phillips curve relates average output gap to average wage inflation: it is virtually vertical at high inflation and flattens at low inflation. Macroeconomic volatility shifts the curve outwards and reduces output. The results imply that stabilization policies play an important role, and that optimal inflation may be positive and differ across countries with different macroeconomic volatility. Results are robust to relaxing the wage constraint, for example, when large idiosyncratic shocks arise. (JEL E23, E24, E31, E63)

Bayesian Estimation of DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
Likelihood Function ◽  
Academic Research ◽  
Dynamic Stochastic General Equilibrium ◽  
Computational Techniques ◽  
Dsge Models ◽  
Monte Carlo Techniques ◽  
Dynamic Stochastic ◽  
Theoretical Foundations

Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. The book is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

Modelling the UK Banking Sector

2010 ◽  
Vol 214 ◽  
pp. F67-F72
Author(s):  
Ray Barrell ◽  
Simon Kirby ◽  
E. Philip Davis
Keyword(s):  
Banking Sector ◽  
National Income ◽  
Financial System ◽  
Financial Sector ◽  
Equation Model ◽  
Dsge Models ◽  
Real Economy ◽  
Equilibrium Models ◽  
Return To Equilibrium ◽  
Dynamic Stochastic

The financial crisis that emerged during 2007 and overwhelmed the financial system in late 2008 also brought to the fore some of the obvious failings of the style of modelling that had been fashionable in central banks in the previous decade. The shift to Dynamic Stochastic General Equilibrium models (DSGE) of whatever sort left no real scope for money and financial markets to have an impact on the real economy. This was in part because equilibrium models based on theory are unlikely to be designed to cope with a period of disequilibrium, which is when the financial system becomes important in macroeconomics. DSGE models come in various guises, and it was common to operate with a three-equation model with demand, supply and the interest rate as the equations. It is hard to see how the financial sector could fit into this, or what use it would be even if it were included. Larger DSGE models that respect the national income identity are easier to augment with a financial sector; but even that developed by the US Federal Reserve (see Edge, Kiley and Laforte, 2010) tends to return to equilibrium rather more rapidly than seems reasonable.

Modelling Monetary Policy

2021 ◽  
pp. 293-316
Author(s):  
Juan Antonio Morales ◽  
Paul Reding
Keyword(s):  
Monetary Policy ◽  
Policy Analysis ◽  
Policy Decision ◽  
Central Banks ◽  
Dynamic Stochastic General Equilibrium ◽  
Dsge Models ◽  
Dynamic Stochastic ◽  
Policy Decision Making

This last chapter deals with the toolbox that central banks use to design and implement their monetary policy strategy. Central banks develop various types of model, both for forecasting and for policy analysis. The chapter discusses the main characteristics of the models used, their strengths and limitations. It assesses how dynamic stochastic general equilibrium (DSGE) models are used for monetary policy analysis. Examples are provided on how they contribute to explore fundamental, long-term policy issues specific to LFDCs. The chapter also discusses the contribution of small semi-structural models which, though less strongly theory grounded than DSGE models, can be brought closer to the available data and are therefore possibly better suited to the context of LFDCs. Attention is also drawn to the key role of judgement as the indispensable complement, in monetary policy decision-making, to model-based policy analysis.

scholarly journals On DSGE Models

2018 ◽  
Vol 32 (3) ◽  
pp. 113-140 ◽  
Author(s):  
Lawrence J. Christiano ◽  
Martin S. Eichenbaum ◽  
Mathias Trabandt
Keyword(s):  
Financial Crisis ◽  
General Equilibrium ◽  
Policy Change ◽  
Great Recession ◽  
Relative Strength ◽  
Dynamic Stochastic General Equilibrium ◽  
Dsge Models ◽  
The Great Recession ◽  
Dynamic Stochastic ◽  
Different Parts

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

scholarly journals The Euler equation with habits and measurement errors: Estimates on Russian micro data

2016 ◽  
Vol 63 (4) ◽  
pp. 395-409 ◽  
Author(s):  
Irina Khvostova ◽  
Alexander Larin ◽  
Anna Novak
Keyword(s):  
Euler Equation ◽  
Measurement Errors ◽  
Generalized Method Of Moments ◽  
Dynamic Stochastic General Equilibrium ◽  
Dsge Models ◽  
Elasticity Of Intertemporal Substitution ◽  
Russian Economy ◽  
Lm Test ◽  
Dynamic Stochastic ◽  
Micro Level

This paper presents estimates of the consumption Euler equation for Russia. The estimation is based on micro-level panel data and accounts for the heterogeneity of agents? preferences and measurement errors. The presence of multiplicative habits is checked using the Lagrange multiplier (LM) test in a generalized method of moments (GMM) framework. We obtain estimates of the elasticity of intertemporal substitution and of the subjective discount factor, which are consistent with the theoretical model and can be used for the calibration and the Bayesian estimation of dynamic stochastic general equilibrium (DSGE) models for the Russian economy. We also show that the effects of habit formation are not significant. The hypotheses of multiplicative habits (external, internal, and both external and internal) are not supported by the data.

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