Forecasting the Australian economy with DSGE and BVAR models

Reflecting the importance of commodities for the Australian economy, we construct a dynamic stochastic general equilibrium (DSGE) model of the Australian economy with a commodity sector. We assess whether its forecasts can be improved by using it as a prior for an empirical Bayesian vector autoregression (BVAR). We find that the forecasts from the BVAR tend to be more accurate than those from the DSGE model. Nevertheless, for output growth these forecasts do not outperform benchmark models, such as a small open economy BVAR estimated using the standard priors for forecasting. A Bayesian factor augmented vector autoregression produces the most accurate near-term inflation forecasts.     

The Macro Pedagogy Debate: Teaching DSGE to Undergraduates Symposium

Dynamic stochastic general equilibrium (DSGE) models have become the workhorse of modern macroeconomics and the standard way to communicate ideas among applied macroeconomists. Undergraduate students, however, often remain unaware of their existence. The lack of specialized knowledge can hurt them if they decide to attend graduate school. Indeed, many first-year PhD students discover that the material they are currently learning differs significantly from what they mastered in college. But this can change. In this article, the author describes how to teach a full-fledged macroeconomics course where DSGE models take center stage. He discusses how to arrange such a course within a one-semester time frame, details the main components of instruction, and finishes with some thoughts based on his teaching experience at Macalester College.     

Model selection in macroeconomics: DSGE and ad hocness

ABSTRACT

We investigate the applicability of Rodrik’s accounts of model selection and horizontal progress to macroeconomic DSGE modelling in both academic and policy-oriented modelling contexts. We argue that the key step of identifying critical assumptions is complicated by the interconnectedness of the common structural core of DSGE models and by the ad hoc modifications introduced to model various rigidities and other market imperfections. We then outline alternative ways in which macroeconomic modelling could become more horizontally progressive.     

The effect of observables,functional specifications,model features and shocks on identification in linearized DSGE models

The decisions a researcher makes at the model building stage are crucial for parameter identification. This paper contains a number of applied tips for solving identifiability problems and improving the strength of DSGE model parameter identification by fine-tuning the (1) choice of observables, (2) functional specifications, (3) model features and (4) choice of structural shocks. We offer a formal approach based on well-established diagnostics and indicators to uncover and address both theoretical (yes/no) identifiability issues and weak identification from a Bayesian perspective. The concepts are illustrated by two exemplary models that demonstrate the identification properties of different investment adjustment cost specifications and output-gap definitions. Our results provide theoretical support for the use of growth adjustment costs, investment-specific technology, and partial inflation indexation.     

Is neo-Walrasian macroeconom(etr)ics a dead end? An assessment of recent criticisms of DSGE models

After the 2008 “new Great Crisis,” it is widely recognized that mainstream macroeconom(etr)ics—the last result of Lucas’s anti-Keynesian revolution of the 1980s, which tried to give macroeconomics sound neo‐Walrasian microeconomic bases —has failed to anticipate and then appraise the crisis. Has this crisis revealed a failure of this macroeconom(etr)ics as a scientific theory? Mainstream macroeconomists defend their models on the basis of their alleged superiority in terms of clarity and coherence. The thesis of this article is that this claim about superiority is false. The study argues that the reasons for the failure of mainstream macroeconom(etr)ics—in particular its poor predictive performance and interpretative weakness—reside in the implications of the neo-Walrasian legacy and the problems connected with the implementation of that program.     

A DSGE model of China

We use available methods for testing macro models to evaluate a model of China over the period from Deng Xiaoping’s reforms up until the crisis period. Bayesian ranking methods are heavily influenced by controversial priors on the degree of price/wage rigidity. When the overall models are tested by Likelihood or Indirect Inference methods, the New Keynesian model is rejected in favour of one with a fair-sized competitive product market sector. This model behaves quite a lot more ‘flexibly’ than the New Keynesian.     

An estimated two-country DSGE model of Austria and the Euro Area

We present a two-country New Open Economy Macro model of the Austrian economy within the European Union’s Economic & Monetary Union (EMU). The model includes both nominal and real frictions that have proven to be important in matching business cycle facts, and that allow for an investigation of the effects and cross-country transmission of a number of structural shocks: shocks to technologies, shocks to preferences, cost-push type shocks and policy shocks. The model is estimated using Bayesian methods on quarterly data covering the period of 1976:Q2–2005:Q1. In addition to the assessment of the relative importance of various shocks, the model also allows to investigate effects of the monetary regime switch with the final stage of the EMU and investigates in how far this has altered macroeconomic transmission. We find that Austria’s economy appears to react stronger to demand shocks, while in the rest of the Euro Area supply shocks have a stronger impact. Comparing the estimations on pre-EMU and EMU subsamples we find that the contribution of (rest of the) Euro Area shocks to Austria’s business cycle fluctuations has increased significantly.

Macroeconomic impacts of fiscal policy shocks in the UK: A DSGE analysis

This paper develops and estimates a new-Keynesian dynamic stochastic general equilibrium (DSGE) model for the analysis of fiscal policy in the UK. We find that government consumption and investment yield the highest GDP multipliers in the short-run, whereas capital income tax and public investment have dominating effect on GDP in the long-run. When nominal interest rate is at the zero lower bound, consumption taxes and public consumption and investment are found to be the most effective fiscal instruments throughout the analysed horizon, and capital and labour income taxes are established to be the least effective. The paper also shows that the effectiveness of fiscal policy decreases in a small open-economy scenario and that nominal rigidities improve effectiveness of public spending and consumption taxes, whereas decrease that of income taxes.     

Structural heterogeneity or asymmetric shocks? Poland and the euro area through the lens of a two-country DSGE model

This paper presents a two-country model linking Poland and the euro area and applies it for assessment of heterogeneity across these two regions. Overall, our results can be seen as rather inconclusive about the differences in parameters describing agents' decision-making in Poland and in the euro area. On the contrary, we find strong evidence for heterogeneity in terms of volatility and synchronization of shocks hitting both economies. Our results may be viewed as a step towards estimating the costs of Poland's entry to the European Monetary Union, associated with giving up the monetary autonomy and losing benefits from stabilizing movements of the exchange rate.     

DSGE model-based forecasting of modelled and nonmodelled inflation variables in South Africa

Inflation forecasts are a key ingredient for monetary policy-making – especially in an inflation targeting country such as South Africa. Generally, a typical Dynamic Stochastic General Equilibrium (DSGE) only includes a core set of variables. As such, other variables, for example alternative measures of inflation that might be of interest to policy-makers, do not feature in the model. Given this, we implement a closed-economy New Keynesian DSGE model-based procedure which includes variables that do not explicitly appear in the model. We estimate such a model using an in-sample covering 1971Q2 to 1999Q4 and generate recursive forecasts over 2000Q1 to 2011Q4. The hybrid DSGE performs extremely well in forecasting inflation variables (both core and nonmodelled) in comparison with forecasts reported by other models such as AR(1). In addition, based on ex-ante forecasts over the period 2012Q1–2013Q4, we find that the DSGE model performs better than the AR(1) counterpart in forecasting actual GDP deflator inflation.     

A graphical representation of an estimated DSGE model

We write a New Keynesian model as an aggregate demand curve and an aggregate supply curve, relating inflation to output growth. The graphical representation shows how structural shocks move aggregate demand and supply simultaneously. We estimate the curves on US data from 1948 to 2010 and study two recessions: the 2001 recession and the Great Recession of 2008–2009. The Great Recession is explained by a collapse of aggregate demand driven by adverse preference and permanent technology shocks, and expectations of low inflation.     

Structural fiscal balances of the UK: a state-space DSGE approach

This article proposes a new framework to estimate and analyse structural fiscal balances of the UK, by combining the state-space modelling with the Bayesian DSGE modelling. In this way, trends and cycles of aggregate variables can be extracted from data consistently with the macroeconomic theory. A setting of an integrated random walk for the underlying stochastic trends fits the data best. An expansion in government spending can increase nominal fiscal revenue to a certain degree, but the effect is not persistent due to two kinds of crowd-out effects: it crowds out domestic investment; and it pushes up the price of domestic goods and simultaneously crowds out the foreign demand. The shocks to the nominal interest rate, foreign output and the government spending are the three major contributors to the variation of the fiscal revenue cycle.     

Business Cycles in an Estimated DSGE Model of China

A small-scale New-Keynesian dynamic stochastic general equilibrium model is estimated by maximum likelihood method using quarterly data of China. Model specifications and parameter equalities between various competing model variants are addressed by formal statistical hypothesis tests, while implications for business cycle fluctuations are evaluated via a variance decomposition experiment, second-moments matching, and some out-of-sample forecast exercises. It is highlighted that both forward and backward components are important for the dynamics of output, inflation and real balances. The monetary authority will take a sufficient aggressive stance, with a significant lagged response, to the current inflation pressure, while leaving less attention to changes in aggregate output. Variance decomposition reveals that large percentages of variations in real and nominal variables are explained by the highly volatile preference shock and potential output shock, respectively. When nominal and real frictions as well as additional shocks are included, our estimated model overall can successfully reproduce the stylized facts of business cycles in the actual data of China and even frequently outperform those forecasts from an unconstrained VAR.     

基于DSGE模型的我国核心通货膨胀研究

文章以新凯恩斯粘性价格理论为基础,采用DSGE模型,为我国核心通货膨胀指数的核算构建了微观基础,并因此获得了各部门价格指数的最优权重。分析认为：最优的权重受部门价格粘性、随机冲击以及部门产出缺口的价格弹性等因素的影响而变化,随着部门的价格粘性的增加而增加,且随着随机冲击方差的减少而增加,又随着部门产出缺口的价格弹性的增加而增加。与CPI指数相比,由最优权重所核算出来的核心通货膨胀指数更加的平滑稳定,没有剧烈的波动,基本上反映了CPI指数的核心趋势。并且文章的研究结论与侯成琪等(2011)的研究也相一致。因此,文章建议其可以作为我国货币政策制定与实施的具有福利标准的参考锚的。     

Estimating parameters of real business cycle models

The calibration technique is the most common procedure to match the data generated from an equilibrium business cycle model with actual macroeconomic time series. This paper goes a step further and tests and applies a maximum likelihood procedure, in combination with the simulated annealing, to estimate the parameters of a baseline RBC model from U.S. macroeconomic time series data. The procedure is tested on a simulated data set where the parameters are known and then applied to U.S. time series data. This permits us to evaluate the efficiency of the procedure and the extent to which the RBC model is a good representation of macroeconomic data.     

Estimating the effects of forward guidance in rational expectations models

Simulations of forward guidance in rational expectations models should be assessed using the “modest policy interventions” framework introduced by Eric Leeper and Tao Zha. That is, the estimated effects of a policy intervention should be considered reliable only if that intervention is unlikely to trigger a revision in private sector beliefs about the way that monetary policy will be conducted. I show how to constrain simulations of forward guidance to ensure that they are regarded as modest policy interventions and illustrate the technique using a medium-scale DSGE model estimated on US data. I find that many experiments that generate the large responses of macroeconomic variables deemed implausible by many economists – the so-called “forward guidance puzzle” – are not modest policy interventions. Those experiments should therefore be treated with caution, since they may prompt agents to believe that there has been a change in the monetary policy regime that is not accounted for within the model. More reliable results can be obtained by constraining the experiment to be a modest policy intervention. In the cases I study, the quantitative effects on macroeconomic variables are more plausible when this constraint is imposed.     

技术冲击、二氧化碳排放与中国经济波动——基于DSGE模型的数值模拟

文章通过构建包含环境约束的动态随机一般均衡模型,分析了生产技术和环保技术冲击对一国主要宏观变量的影响。研究发现:(1)生产技术冲击对经济发展的促进作用是直接的、主要的,而对污染排放量的增长效应则是间接的、次要的,最优污染排放变动具有顺周期性;(2)环保技术冲击对经济的推动作用是间接的、次要的,而对污染排放量的限制作用则是直接的、主要的,最优污染排放变动具有逆周期性;(3)在两类冲击共同作用下,环保技术冲击的减排效应短期显著,而生产技术冲击的增长效应则长期占优,但两类冲击对全球污染存量变动的影响都十分微弱,经济波动周期维持在十年左右。     

The transmission of financial shocks in an estimated DSGE model with housing and banking

We develop a dynamic stochastic general equilibrium (DSGE) model with housing and banking to study the transmission of financial shocks between the financial and real sectors. A deterioration in the bank's balance sheet induced by financial shocks could have amplified and persistent impacts on real activities. The amplification of the shocks are originated from financial frictions tied to households and banks. We find that a disruption in bank net worth initiated by capital quality shocks generates a decline in household loans, house prices and output. Bank liquidity shocks also have negative effects on these variables. Housing preference shocks could generate a positive comovement between house prices and output. All these findings are qualitatively consistent with empirical evidence, suggesting that these financial shocks are critical to the dynamics of house prices and other macroeconomic variables.     

Yield curve and the macroeconomy: Evidence from a DSGE model with housing

The slope of the yield curve has long been found to be a useful predictor of future economic activities, but the relationship is unstable. One change we have identified in this paper is that, between the early 1990s and the collapse of the housing market in 2007, movements at the long end of the yield curve have an increase in predictive power. We use a medium-scale DSGE model with a housing sector and a yield curve as a guide to find out the sources of such change. The model implies that an increase in the short-term interest rate and a decrease in the long-term interest rate have different impacts on the economy, and to use the slope as a predictor one needs to distinguish movements at the two ends of the yield curve. Based on simulated data from the model, we find that nominal wage rigidities and the capital adjustment costs are closely related to the predictive power of the yield curve. This result is further confirmed with actual data.     

On the predictability of time-varying VAR and DSGE models

Over the last few years, there has been a growing interest in DSGE modelling for predicting macroeconomic fluctuations and conducting quantitative policy analysis. Hybrid DSGE models have become popular for dealing with some of the DSGE misspecifications as they are able to solve the trade-off between theoretical coherence and empirical fit. However, these models are still linear and they do not consider time variation for parameters. The time-varying properties in VAR or DSGE models capture the inherent nonlinearities and the adaptive underlying structure of the economy in a robust manner. In this article, we present a state-space time-varying parameter VAR model. Moreover, we focus on the DSGE–VAR that combines a microfounded DSGE model with the flexibility of a VAR framework. All the aforementioned models as well simple DSGEs and Bayesian VARs are used in a comparative investigation of their out-of-sample predictive performance regarding the US economy. The results indicate that while in general the classical VAR and BVARs provide with good forecasting results, in many cases the TVP–VAR and the DSGE–VAR outperform the other models.