permanent income hedonic prices and demand for housing new evidence abstract housing demand is examined by looking quite specifically at the income and price variables based on individual household data permanent and transitory incomes are computed through instrumental variables related to human and nonhuman wealth a price is constructed by spatially varying hedonic techniques separation of measured income into permanent and transitory components substantially improves the predictive power of the housing demand estimation and leads to demand elasticities of 1 and 1 with respect to permanent income and price the permanent income elasticity is roughly twice the measured income elasticity

the determinants of homeownership affordability among the sandwich class empirical findings from guangzhou china the sandwich class is an east asian term referring to the lower middle class using a large and unique micro dataset collected in guangzhou this paper examines empirically the potential determin

macroeconomic forecasting in the euro area country specific versus area wide information abstract this paper compares several time series methods for short run forecasting of euro wide inflation and real activity using data from 1982 to 1997 forecasts are constructed from univariate autoregressions vector autoregressions single equation models that include euro wide and us aggregates and large model methods in which forecasts are based on estimates of common dynamic factors aggregate euro wide forecasts are constructed from models that utilize only aggregate euro wide variables and by aggregating country specific models the results suggest that forecasts constructed by aggregating the country specific models are more accurate than forecasts constructed using the aggregate data

locating chinese urban housing policy in an international context china s economic development has often been contrasted with that of other transition economies in europe but academics have fought shy of making direct comparisons of urban housing reform in the two systems this paper fills this gap by making such direct comparisons adopting the market housing model advocated by the world bank as an analytical framework it finds that extensive housing privatisation in china is supported by a system of urban housing property rights and a growing residential mortgage market although china has a distinctive institutional framework there is also much variety among the european transition countries and a distinctive chinese model was not identified so this micro level analysis did not support the contention that china represents a form of contested modernity nonetheless a crucial point arises from china s hybrid status as a developing as well as a transition country the bulk of the urban migrant population remains excluded from formal housing policy and enabling st

housing choice hindrances and urban spatial structure evidence from matched location and location preference data in chinese cities abstract in a monocentric city with a well functioning residential market pareto efficient spatial equilibrium entails the sorting of residents according to their bid rent gradient in descending order away from city center violation of this sorting condition creates opportunities for pareto improving trading of locations and can be sustained only if the market is hindered we propose a simple ordered location choice model using matched location and location preference data of individual households to examine violations of the pareto efficient spatial sorting condition in so doing we are able to identify population groups facing housing choice hindrances we find in a sample of chinese cities undergoing housing market liberalization that poor marketability of the previously state provided homes inadequate provision of housing finance and spatial mismatch between job market and housing market opportunities contribute to a pareto inefficient spatial structure

the fund flow approach a critical survey the fund ow approach to production theory was proposed by nicholas georgescu roegen almost half a century ago and it provides a description of production as a process unfolding in time and entailing a temporal coordination between dierent elements despite the initial interest the approach has seldom received attention by mainstream economists and it is not yet well known the paper critically surveys georgescu roegen s model together with i the later developments and modications ii the recent criticisms focused on its limitations due to the instrumental assumption of constant eciency for funds the paper concludes by discussing the limits and comparative merits and suggesting possible applications

multivariate density forecast evaluation and calibration in financial risk management high frequency returns on foreign exchange we provide a framework for evaluating and improving multivariate density forecasts among other things the multivariate framework lets us evaluate the adequacy of density forecasts involving cross variable interactions such as time varying conditional correlations we also provide conditions under which a technique of density forecast calibration can be used to improve deficient density forecasts and we show how the calibration method can be used to generate good density forecasts from econometric models even when the conditional density is unknown finally motivated by recent advances in financial risk management we provide a detailed application to multivariate high frequency exchange rate density forecasts

inflation output variance trade offs and optimal monetary policy the author estimates the inflation output gap variance trade off faced by monetary policymakers in the united states for policymakers who care about deviations of inflation around target and output around potential the estimated trade off represents the optimal policy frontier given the structure of the economy policymakers can do no better than to attain weighted variances of inflation and output that lie on the frontier the author finds that the variance trade off becomes quite severe when the standard deviation of inflation or output drops much below 2 percent this suggests that approximately balanced responses to policy goals are consistent with reasonable preferences over inflation and output variability copyright 1997 by ohio state university press

measures of per capita hours and their implications for the technology hours debate structural vector autoregressions give conflicting results on the effects of technology shocks on hours the results depend crucially on the assumed data generating process for hours per capita we show that the standard measure of hours per capita and productivity have significant low frequency movements that are the source of the conflicting results hodrick prescott hp filtered hours per capita produce results consistent with those obtained when hours are assumed to have a unit root we show that important sources of the low frequency movements in the standard measure are sectoral shifts in hours and the changing age composition of the working age population when we control for these low frequency components to determine the effect of technology shocks on hours using long run restrictions we get one consistent answer hours decline in the short run in response to a positive technology shock we further extend the analysis by examining the effects of demographic controls on the impulse responses to investment specific technology shocks our results are less conclusive

prediction with misspecified models many decision makers in the public and private sectors routinely consult the implications of formal economic and statistical models in their work especially in large organizations and for important decisions there are often competing models of course no model under consider ation is a literal representation of reality for the purposes at hand more succinctly no model is true and different models focus on different aspects of the relevant environment this fact can often be supported by formal econometric tests concluding that the models at hand are indeed misspecified in various dimensions there are well developed practical bayesian procedures with solid theoretical foundations for combining competing models in decisionmaking geweke 2005 section 1 5 but these procedures all condition on one of the models under consideration being true non bayesian model selection procedures may be less formal but proceed under the same maintained hypothesis this leads to the common situation in which decision makers are left to balance informally the various predictions and decisions that are formal consequences of competing economic and statistical models in this circumstance serious attention is typically granted to the implications of models to which formal econometric procedures assign very little credence the approach taken here draws on a literature long established in statistics and recently emerging in econometrics that dispenses with the condition that one of the models under consider ation is true in its place it substitutes a log scor

monetary policy rules based on real time data this paper examines the magnitude of informational problems associated with the implementation and interpretation of simple monetary policy rules using taylor s rule as an example i demonstrate that real time policy recommendations differ considerably from those obtained with ex post revised data further estimated policy reaction functions based on ex post revised data provide misleading descriptions of historical policy and obscure the behavior suggested by information available to the federal reserve in real time these results indicate that reliance on the information actually available to policy makers in real time is essential for the analysis of monetary policy rules

supplanting the minnesota prior forecasting macroeconomic time series using real business cycle model priors abstract although general equilibrium models are in wide use in the theoretical macroeconomic literature their empirical relevance is uncertain we develop procedures for using dynamic general equilibrium models to aid in analyzing the observed time series relationships among macroeconomic variables our strategy is based on that developed by doan litterman and sims 1984 who constructed a procedure for improving time series forecasts by shrinking vector autoregression coefficient estimates toward a prior view that vector time series are well described as collections of independent random walks in our case the prior is derived from a fully specified general equilibrium model we demonstrate that like the atheoretical random walk priors real business cycle model priors can aid in forecasting

an econometric model of housing price permanent income tenure choice and housing demand abstract this paper addresses the determination of housing price permanent income tenure choice and housing demand full housing demand elasticities incorporate the interactive effects among the four stages of the model price and income have major effects in the tenure choice equation sociodemographic variables such as age have complex effects that may be lost in simpler forms of estimation

federal reserve information and the behavior of interest rates this paper tests for the existence of asymmetric information between the federal reserve and the public by examining federal reserve and commercial inflation forecasts it demonstrates that the federal reserve has considerable information about inflation beyond what is known to commercial forecasters it also shows that monetary policy actions provide signals of the federal reserve s information and that commercial forecasters modify their forecasts in response to those signals these findings may explain why long term interest rates typically rise in response to shifts to tighter monetary policy jel e52 e43 d82 asymmetric information between the federal reserve and the public is a phenomenon that is often posited but rarely tested numerous models of central bank behavior for example show that the existence of asymmetric information has important implications for the effectiveness of policy and the consequences of dynamic inconsistency yet there

evaluating point and density forecasts of dsge models this paper investigates the accuracy of point and density forecasts of four dsge models for inflation output growth and the federal funds rate model parameters are estimated and forecasts are derived successively from historical u s data vintages synchronized with the fed s greenbook projections point forecasts of some models are of similar accuracy as the forecasts of nonstructural large dataset methods despite their common underlying new keynesian modeling philosophy forecasts of different dsge models turn out to be quite distinct weighted forecasts are more precise than forecasts from individual models the accuracy of a simple average of dsge model forecasts is comparable to greenbook projections for medium term horizons comparing density forecasts of dsge models with the actual distribution of observations shows that the models overestimate uncertainty around point forecasts

the developing world s bulging but vulnerable middle class summary western notions of the middle class are of little obvious relevance to developing countries instead the middle class is identified here as those living above the median poverty line of developing countries even if still poor by rich country standards over 1990 2005 economic growth and global distributional shifts allowed an extra 1 2 billion people to join the developing world s middle class four fifths came from asia and half from china many of those in this new middle class remain fairly close to poverty only 100 million of the 1 2 billion would not be considered poor in any developing county economic growth typically came with an expanding middle class

evaluating density forecasts with applications to financial risk management density forecasting is increasingly more important and commonplace for example in financial risk management yet little attention has been given to the evaluation of density forecasts the authors develop a simple and operational framework for density forecast evaluation they illustrate the framework with a detailed application to density forecasting of asset returns in environments with time varying volatility finally the authors discuss several extensions copyright 1998 by economics department of the university of pennsylvania and the osaka university institute of social and economic research association

labor income uncertainty skewness and homeownership a panel data study for germany and spain abstract in this paper we empirically investigate the effect of labor income uncertainty on the probability of homeownership in germany and spain this study is motivated by two facts firstly theoretical models tend to provide ambiguous results on this issue secondly previous empirical evidence focuses exclusively on the us housing market to carry out our analysis we propose more precise income uncertainty measures based on panel data labor income equations we observe that households facing high levels of income uncertainty display a preference for renting while those located in more positively skewed income distributions show a greater propensity for homeownership

monetary policy trade offs and the correlation between nominal interest rates and real output the authors present a structural model of the u s economy that combines their price contracting specification with a term structure relationship an aggregate demand curve and a monetary policy reaction function the model matches important features of postwar data well and provides a structural explanation of the correlation between real output and the short term nominal rate of interest the authors perform a battery of monetary policy experiments that show that as viewed through the lens of this model monetary policy has struck a good balance recently among competing monetary policy objectives copyright 1995 by american economic association

a comparison of forecast performance between federal reserve staff forecasts simple reduced form models and a dsge model this paper considers the forecast performance of the federal reserve staff five atheoretical reduced form models and an estimated dynamic stochastic general equilibrium dsge model focusing on the late 1990s through 2001 our analysis finds that the dsge model and atheoretical models forecast real gdp growth better than the federal reserve staff during this period by an economically significant margin we find smaller differences across each method in the quality of inflation forecasts over this period these results provide some support to the notion that richly specified dsge models such the one used in this paper belong in the forecasting toolbox of a central bank rochelle m edge rochelle m edge frb gov michael t kiley michael t kiley frb gov and jeanphilippe laforte jean philippe laforte frb gov are affiliated with the macroeconomic and quantitative studies section at the board of governors of the federal reserve system this paper represents ongoing work in the section on developing dge models that can be useful for policy analysis nevertheless any views expressed in this paper remain solely those of the authors and do not necessarily reflect those of the board of governors of the federal reserve system or it staff all errors are our own

monetary policy in a data rich environment abstract most empirical analyses of monetary policy have been confined to frameworks in which the federal reserve is implicitly assumed to exploit only a limited amount of information despite the fact that the fed actively monitors literally thousands of economic time series this article explores the feasibility of incorporating richer information sets into the analysis both positive and normative of fed policymaking we employ a factor model approach developed by stock j h watson m w diffusion indices journal of business economic statistics 2002 20 2 147 forecasting inflation 1999 journal of monetary economics 44 2 293 that permits the systematic information in large data sets to be summarized by relatively few estimated factors with this framework we reconfirm stock and watson s result that the use of large data sets can improve forecast accuracy and we show that this result does not seem to depend on the use of finally revised as opposed to real time data we estimate policy reaction functions for the fed that take into account its data rich environment and provide a test of the hypothesis that fed actions are explained solely by its forecasts of inflation and real activity finally we explore the possibility of developing an expert system that could aggregate diverse information and provide benchmark policy settings

do financial variables help forecasting inflation and real activity in the euro area abstract this paper uses a large data set consisting of 447 monthly macroeconomic time series concerning the main countries of the euro area to simulate out of sample predictions of the euro area industrial production and the harmonized inflation index and to evaluate the role of financial variables in forecasting we considered two models which allow forecasting based on large panels of time series forni et al rev econom statist 82 2000 540 mimeo 2001b and stock and watson mimeo 1999 performance of both models were compared to that of a simple univariate ar model results show that multivariate methods outperform univariate methods for forecasting inflation at one three six and twelve months and industrial production at one and three months we find that financial variables do help forecasting inflation but do not help forecasting industrial production

priors from general equilibrium models for vars abstract this paper uses a simple new keynesian dynamic stochastic general equilibrium model as a prior for a vector autoregression shows that the resulting model is competitive with standard benchmarks in terms of forecasting and can be used for policy analysis jel classification c11 c32 c53 key words bayesian analysis dsge models forecasting vector autoregressions 1 introduction dynamic stochastic general equilibrium dsge models are popular nowadays in macroeconomics they are taught in virtually every economics ph d program and represent a predominant share of publications in the field yet when it comes to policy making these models are scarcely used at least from a quantitative point of view the main quantitative workhorse for policy making at the federal reserve system is frb us a macro econometric model built in the cowles foundation tradition a style of macroeconomics that is no longer taught in many ph d programs 1 in their decision process fed policy makers rely heavily on forecasting they want to know the expected path of inflation in the next few quarters and by how much a 50 basis point increase in the federal funds rate would affect that path frb us offers answers to these questions answers that many macroeconomists would regard with suspicion given both the lucas 1976 critique and the fact that in general the restrictions imposed by cowles foundation models are at odds with dynamic general equilibrium macroeconomics sims 1980 general equilibrium models on the other hand have a hard time providing alternative answers the fact that these models are perceived to do badly in terms of forecasting as they are scarcely parameterized is perhaps one of the reasons why they are not at the forefront of policy making while progress is being made in the development of dsge models that deliver acceptable forecasts e g smets and wouters 2003 this paper proposes an approach that combines a stylized general equilibrium model with a vector autoregression var to obtain a specification that both forecasts well and is usable for policy analysis specifically the approach involves using prior information coming from a dsge model in the estimation of a vector autoregression loosely speaking this prior can be thought of as the result of the following exercise i simulate time series data from the dsge model ii fit a var to these data in practice we replace the sample moments of the simulated data by population moments computed from the dsge model solution since the dsge model depends on unknown structural parameters we use a hierarchical prior in our analysis by placing a distribution on the dsge model parameters a tightness parameter controls the weight of the dsge model prior relative to the weight of the actual sample markov chain monte carlo methods are used to generate draws from the joint posterior distribution of the var and dsge model parameters the paper shows that the approach makes even a fairly stylized new keynesian dsge model competitive with standard benchmarks in terms of forecasting real output growth inflation and the nominal interest rate the three variables that are of most interest to policy makers 2 up to this point our procedure borrows from the work of dejong ingram and whiteman 1993 and ingram and whiteman 1994 who are the first to use priors from dsge models for vars ingram and whiteman showed that prior information from the bare bones stochastic growth model of king plosser and rebelo 1988 is helpful in forecasting real economic activity such as output consumption investment and hours worked in addition to documenting the forecasting performance of a trivariate var with a prior derived from a monetary dsge model this paper makes two contributions that significantly extend the earlier work first we show formally how posterior inference for the var parameters can be translated into posterior inference for dsge model parameters

on the fit of new keynesian models this article provides new tools for the evaluation of dynamic stochastic general equilibrium dsge models and applies them to a large scale new keynesian model we approximate the dsge model by a vector autoregression and then systematically relax the implied cross equation restrictions and document how the model fit changes we also compare the dsge model s impulse responses to structural shocks with those obtained after relaxing its restrictions we find that the degree of misspecification in this large scale dsge model is no longer so large as to prevent its use in day to day policy analysis yet is not small enough to be ignored

combining var and dsge forecast densities a popular macroeconomic forecasting strategy utilizes 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 use the linear opinion pool to combine inflation forecast densities from many vector autoregressions vars and a policymaking dsge model the dsge receives a substantial weight in the pool at 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 but produces well calibrated forecast densities for inflation