The NEP-DGE Blog

This blog is an experiment to explore the feasibility of scientific discussion on an Economics blog. NEP-DGE disseminates every week new working papers in the field of Dynamics General Equilibrium. Among them, the NEP-DGE editor selects one to be discussed. Everyone is invited to comment. Try to stay civil, or your comments will be removed. And encourage others to read or join in the discussion.

DSGE models and forecasting

Putting the New Keynesian DSGE model to the real-time forecasting test

by Marcin Kolasa, Michał Rubaszek and Paweł Skrzypczyński

http://d.repec.org/n?u=RePEc:ecb:ecbwps:20091110&r=dge

Dynamic stochastic general equilibrium models have recently become standard tools for policy-oriented analyses. Nevertheless, their forecasting properties are still barely explored. We fill this gap by comparing the quality of real-time forecasts from a richly-specified DSGE model to those from the Survey of Professional Forecasters, Bayesian VARs and VARs using priors from a DSGE model. We show that the analyzed DSGE model is relatively successful in forecasting the US economy in the period of 1994-2008. Except for short-term forecasts of inflation and interest rates, it is as good as or clearly outperforms BVARs and DSGE-VARs. Compared to the SPF, the DSGE model generates better output forecasts at longer horizons, but less accurate short-term forecasts for interest rates. Conditional on experts’ now casts, however, the forecasting power of the DSGE turns out to be similar or better than that of the SPF for all the variables and horizons.

Combining VAR and DSGE forecast densities

by Ida Wolden Bache, Anne Sofie Jore, James Mitchell and Shaun Vahey

http://d.repec.org/n?u=RePEc:bno:worpap:2009_23&r=dge

A popular macroeconomic forecasting strategy takes combinations across many models to hedge against instabilities of unknown timing; see (among others) Stock and Watson (2004), Clark and McCracken (2010), and Jore et al. (2010). Existing studies of this forecasting strategy exclude Dynamic Stochastic General Equilibrium (DSGE) models, despite the widespread use of these models by monetary policymakers. In this paper, we combine inflation forecast densities utilizing an ensemble system comprising many Vector Autoregressions (VARs), and a policymaking DSGE model. The DSGE receives substantial weight (for short horizons) provided the VAR components exclude structural breaks. In this case, the inflation forecast densities exhibit calibration failure. Allowing for structural breaks in the VARs reduces the weight on the DSGE considerably, and produces well-calibrated forecast densities for inflation.

Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals

by Rangan Gupta, Alain Kabundi and Stephen Miller

http://d.repec.org/n?u=RePEc:pre:wpaper:200927&r=dge

We employ a 10-variable dynamic structural general equilibrium model to forecast the US real house price index as well as its turning point in 2006:Q2. We also examine various Bayesian and classical time-series models in our forecasting exercise to compare to the dynamic stochastic general equilibrium model, estimated using Bayesian methods. In addition to standard vector-autoregressive and Bayesian vector autoregressive models, we also include the information content of either 10 or 120 quarterly series in some models to capture the influence of fundamentals. We consider two approaches for including information from large data sets – extracting common factors (principle components) in a Factor-Augmented Vector Autoregressive or Factor-Augmented Bayesian Vector Autoregressive models or Bayesian shrinkage in a large-scale Bayesian Vector Autoregressive models. We compare the out-of-sample forecast performance of the alternative models, using the average root mean squared error for the forecasts. We find that the small-scale Bayesian-shrinkage model (10 variables) outperforms the other models, including the large-scale Bayesian-shrinkage model (120 variables). Finally, we use each model to forecast the turning point in 2006:Q2, using the estimated model through 2005:Q2. Only the dynamic stochastic general equilibrium model actually forecasts a turning point with any accuracy, suggesting that attention to developing forward-looking microfounded dynamic stochastic general equilibrium models of the housing market, over and above fundamentals, proves crucial in forecasting turning points.

Perhaps by coincidence, three new papers in this week’s issue of the NEP-DGE report deal with forecasting. Kolasa, Rubaszek and Skrzypczyński says that DSGE models perform remarkably well. Bache, Jore, Mitchell and Vahey claim that VAR models with structural breaks do better, but of course structural breaks cannot be predicted with a VAR. Gupta, Kabundi and Miller show that DSGE models of real estate markets are better with turning points, which are the most difficult statistic to forecast.

Labor Supply Heterogeneity and Macroeconomic Co-movement

by Stefano Eusepi and Bruce Preston

http://d.repec.org/n?u=RePEc:nbr:nberwo:15561&r=dge

Standard real-business-cycle models must rely on total factor productivity (TFP) shocks to explain the observed co-movement between consumption, investment and hours worked. This paper shows that a neoclassical model consistent with observed heterogeneity in labor supply and consumption, can generate co-movement in absence of TFP shocks. Intertemporal substitution of goods and leisure induces co-movement over the business cycle through heterogeneity in consumption behavior of employed and unemployed workers. The result is due to two model features that are introduced to capture important characteristics of US labor market data. First, individual consumption is affected by the number of hours worked with employed consuming more on average than unemployed. Second, changes in the employment rate, a central explanator of total hours variation, then affects aggregate consumption. Demand shocks — such as shifts in the marginal efficiency of investment, government spending shocks and news shocks — are shown to generate economic fluctuations consistent with observed business cycles.

A critical aspect of any business cycle model is the (intertemporal) substitution between consumption and leisure. In particular, this drives to a large extend the correlations between labor, consumption and investment. Traditional TFP based models have been critized for getting some of these correlations wrong, unless wealth effects are assumed away. This model is an attempt to replicate these correlations without TFP shocks and adopted a household whose members are unemployed in proportions varying through the business cycle.

Lending Relationships and Monetary Policy

by Yunus Aksoy, Henrique S. Basso and Javier Coto-Martinez

http://d.repec.org/n?u=RePEc:bbk:bbkefp:0912&r=dge

Financial intermediation and bank spreads are important elements in the analysis of business cycle transmission and monetary policy. We present a simple framework that introduces lending relationships, a relevant feature of financial intermediation that has been so far neglected in the monetary economics literature, into a dynamic stochastic general equilibrium model with staggered prices and cost channels. Our main findings are: (i) banking spreads move countercyclically generating amplified output responses, (ii) spread movements are important for monetary policy making even when a standard Taylor rule is employed (iii) modifying the policy rule to include a banking spread adjustment improves stabilization of shocks and increases welfare when compared to rules that only respond to output gap and inflation, and finally (iv) the presence of strong lending relationships in the banking sector can lead to indeterminacy of equilibrium forcing the central bank to react to spread movements.

There has been relatively little work on lending relationships, primarily because it is a very hard problem to model and solve. Here is a fresh attempt that seems rather successful.

Inflation and Welfare in Long-Run Equilibrium with Firm Dynamics

By Alexandre Janiak and Paulo Santos Monteiro

http://d.repec.org/n?u=RePEc:iza:izadps:dp4559&r=dge

We analyze the welfare cost of inflation in a model with cash-in-advance constraints and an endogenous distribution of establishments’ productivities. Inflation distorts aggregate productivity through firm entry dynamics. The model is calibrated to the United States economy and the long-run equilibrium properties are compared at low and high inflation. We find that, when the period over which the cash-in-advance constraint is binding is one quarter, an annual inflation rate of 10 percent leads to a decrease in the steady-state average productivity of roughly 0.5 percent compared to the optimum’s steady-state. This decrease in productivity is not innocuous: it leads to a doubling of the welfare cost of inflation.

It has been very difficult to find substantial costs for inflation, in a large part because it is difficult to make money matter in significant ways in a microfounded model. This attempt is different in that the welfare cost comes from productivity losses through the firm entry and distribution. The resulting impact of money and inflation is indirect yet important.

Portfolio inertia and the equity premium

By Christopher Gust and David López-Salido

http://d.repec.org/n?u=RePEc:fip:fedgif:984&r=dge

We develop a DSGE model in which aggregate shocks induce endogenous movements in risk. The key feature of our model is that households rebalance their financial portfolio allocations infrequently, as they face a fixed cost of transferring cash across accounts. We show that the model can account for the mean returns on equity and the risk-free rate, and generates countercyclical movements in the equity premium that help explain the response of stock prices to monetary shocks. The model is consistent with empirical evidence documenting that unanticipated changes in monetary policy have important effects on equity prices through changes in risk.

Yet another attempt to solve the equity premium puzzle while obtaining a reasonable risk free rate. So many explanation have been thrown at the wall, finally a explanation that will stick?

Credit Constraints and the Persistence of Unemployment

By Nicolas Dromel, Elie Kolakez and Etienne Lehmann

http://d.repec.org/n?u=RePEc:iza:izadps:dp4501&r=dge

In this paper, we argue that credit market imperfections impact not only the level of unemployment, but also its persistence. For this purpose, we first develop a theoretical model based on the equilibrium matching framework of Mortensen and Pissarides (1999) and Pissarides (2000) where we introduce credit constraints. We show these credit constraints not only increase steady-state unemployment, but also slow down the transitional dynamics. We then provide an empirical illustration based on a country panel dataset of 20 OECD countries. Our results suggest that credit market imperfections significantly increase the persistence of unemployment.

This paper combines (imperfect) credit markets and labor market frictions. The innovation is that entrepreneurs need to borrow to create jobs, but can do so only up to a fraction of pledgeable assets. The consequences that unemployment level and persistence are dependent on the sophistication of credit markets. While this is empirically consistent, is this a credible model of entrepreneurship and job creation?

Housing and Debt Over the Life Cycle and Over the Business Cycle

By Matteo Iacoviello and Marina Pavan

http://d.repec.org/n?u=RePEc:boc:bocoec:723&r=dge

We present an equilibrium life-cycle model of housing where nonconvex adjustment costs lead households to adjust their housing choice infrequently and by large amounts when they do so. In the cross-sectional dimension, the model matches the wealth distribution, the age profiles of consumption, homeownership, and mortgage debt, and data on the frequency of housing adjustment. In the time-series dimension, the model accounts for the procyclicality and volatility of housing investment, and for the procyclical behavior of household debt. We use a calibrated version of our model to ask the following question: what are the consequences for aggregate volatility of an increase in household income risk and a decrease in downpayment requirements? We distinguish between an early period, the 1950s through the 1970s, when household income risk was relatively small and loan-to-value ratios were low, and a late period, the 1980s through today, with high household income risk and high loan-to-value ratios. In the early period, precautionary saving is small, wealth-poor people are close to their maximum borrowing limit, and housing investment, homeownership and household debt closely track aggregate productivity. In the late period, precautionary saving is larger, wealth-poor people borrow less than the maximum and become more cautious in response to aggregate shocks. As a consequence, the correlation between debt and economic activity on the one hand, and the sensitivity of housing investment to aggregate shocks on the other, are lower, as is found the data. Quantitatively, our model can explain: (one) 45 percent of the reduction in the volatility of household investment; (two) the decline in the correlation between household debt and economic activity; (three) about 10 percent of the reduction in the volatility of GDP.

This is an innovative model that tries to address issues that go beyond the the housing market: how can innovation in the financing of housing explain the evolution of the volatility of GDP, the volatility of housing investment and the relationship of household debt and economic activity? These issues have previously only been addressed with models where households invest and borrow some generic asset. Housing is different, because of its life-cycle aspect and its lumpiness, and this appears to matter.

About overborrowing

Two somewhat related papers this week.

Overborrowing and systemic externalities in the business cycle

by Javier Bianchi

http://d.repec.org/n?u=RePEc:fip:fedawp:2009-24&r=dge

Credit constraints that link a private agent’s debt to market-determined prices embody a credit externality that drives a wedge between competitive and constrained socially optimal equilibria, inducing private agents to overborrow. The externality arises because agents fail to internalize the debt-deflation effects of additional borrowing when negative income shocks trigger the credit constraint. We quantify the effects of this inefficiency in a two-sector dynamic stochastic general equilibrium model of a small open economy calibrated to emerging markets. The credit externality increases the probability of financial crises by a factor of seven and causes the maximum drop in consumption to increase by 10 percentage points.

Rising indebtedness and hyperbolic discounting: a welfare analysis

by Makoto Nakajima

http://d.repec.org/n?u=RePEc:fip:fedpwp:09-25&r=dge

Is the observed rapid increase in consumer debt over the last three decades good news for consumers? This paper quantitatively studies macroeconomic and welfare implications of relaxing borrowing constraints when consumers exhibit a hyperbolic discounting preference. In particular, the author constructs a calibrated general equilibrium life-cycle model with uninsured idiosyncratic earnings shocks and a quasi-hyperbolic discounting preference and examines the effect of relaxation of the borrowing constraint which generates increased indebtedness. The model can capture the two contrasting views associated with increased indebtedness: the positive view, which links increased indebtedness to financial sector development and better insurance, and the negative view, which associates increased indebtedness with consumers’ over-borrowing. He finds that while there is a welfare gain as large as 0.4 percent of flow consumption from a relaxed borrowing constraint, which is consistent with the observed increase in aggregate debt between 1980 and 2000 in the model with standard exponential discounting consumers, there is a welfare loss of 0.2 percent in the model with hyperbolic discounting consumers. This result holds in spite of the observational similarity of the two models; the macroeconomic implications of a relaxed borrowing constraint are similar between the two models. Cross-sectionally, although consumers of high and low productivity gain and medium productivity consumers suffer due to a relaxed borrowing constraint in both models, the welfare gain of low-productivity consumers is substantially reduced (and becomes negative in the case of strong hyperbolic discounting) in the hyperbolic discounting model due to the welfare loss from over-borrowing. Finally, the author finds that the optimal (social welfare maximizing) borrowing limit is 15 percent of average income, which is substantially lower than both the optimal level implied by the exponential discounting model (37 percent) and the level of the U.S. economy in 2000 implied by the model (29 percent).

The Bianchi paper shows that agents overborrow and this has negative consequences on the economy because of a larger risk of financial crises. The Nakajima paper argues that the observed increase in borrowing may be due to overborrowing due to hyperbolic discounting and financial innovation and the negative welfare effect of hyperbolic discounting dominates. Should one restrain consumer borrowing even if standard model indicate that completing markets should be welfare improving?

Economists, Incentives, Judgment, and the European CVAR Approach to Macroeconometrics

by David Colander

http://d.repec.org/n?u=RePEc:mdl:mdlpap:0912&r=dge

This paper argues that the DSGE approach to macroeconometrics is the dominant approach because it meets the institutional needs of the replicator dynamics of the profession, not because it is necessarily the best way to do macroeconometrics. It further argues that this “DSGE-theory first” approach is inconsistent with the historical approach that economists have advocated in the past and that the alternative European CVAR approach is much more consistent with economist’s historically used methodology, correctly understood. However, because the European CVAR approach requires explicit researcher judgment, it does not do well in the replicator dynamics of the profession. The paper concludes with the suggestion that there should be an increase in dialog between the two approaches.

Is Colander correct in calling for approaches that are consistent with historic approaches to be privileged? Scientific progress is made by trying new approaches, and if they allow old ones to be rejected, then be it. But can we reject these old approaches?

How important is human capital? A quantitative theory assessment of world income inequality

by Andrés Erosa, Tatyana Koreshkova and Diego Restuccia

http://d.repec.org/n?u=RePEc:imd:wpaper:wp2009-11&r=dge

We develop a quantitative theory of human capital investments in order to evaluate the magnitude of cross-country differences in total factor productivity (TFP) that explains the variation in per-capita incomes across countries. We build a heterogeneous-agent economy with cross-sectional variation in ability, schooling, and expenditures on schooling quality. By embedding our analysis in a growth model with tradable and non-tradable sectors, we model sectorial productivity differences across countries, as documented in Hsieh and Klenow (2007). The parameters governing human capital production and random ability and taste processes are restricted by a set of cross-sectional data moments such as variances and intergenerational correlations of earnings and schooling, as well as slope coefficient and R2 in a Mincer regression. Our main finding is that human capital accumulation strongly amplifies TFP differences across countries: To explain a 20-fold difference in the output per worker the model requires a 5-fold difference in the TFP of the tradable sector, versus an 18-fold difference if human capital is fixed across countries. Moreover, we find that sectorial productivity differences play a prominent role in quantitative implications of the theory.

There is plenty of empirical literature trying to establish the importance of human capital in cross-country income differences, usually neglecting that human capital may be endogenous. Clearly, a more structural approach is warranted and this paper delivers this, along with a very rich model. Will this paper convince the cross-country regression enthousiasts?