business cycle analysis with a markov switching model this article explores the hamilton markov switching model through an analysis of the business cycles of eight developed market economies forecasting and specification tests suggest only marginal improvements over linear autoregressive models yet filtered and smoothed conditional probabilities indicate turning points in business cycles that closely correlate with turning points from traditional methods tests regarding the asymmetry of business cycles reject the null of symmetry for most countries

the drivers of international migration to the uk a panel based bayesian model averaging approach a heterogeneous panel based bayesian model averaging approach is used to identify the robust economic and policy drivers of international migration to the uk from 14 different source regions over 1980 2007 around three quarters of the increase in net immigration over the last decade which is particularly pronounced for selected source regions is associated with structural change which may be attributed to uk and foreign immigration policy the remainder of the rise is largely explained by friends and family effects there are considerable uncertainties associated both with the effects of particular economic drivers of immigration and with forecasts of immigration

estimates of output gaps in four southeast asian countries abstract the output gaps derived for four countries using a generalized hamilton model are compared with conventional output gap estimates further research is needed to explain why the output gap identifies crisis episodes as slowdowns instead of recessions in some countries

economic activity and recession probabilities information content and predictive power of the term spread in italy the aim of the present article is to examine the information content of the italian term spread as for real economic growth rates and recession probabilities and to test its predictive power in forecasting regime probabilities to this end the relationship between the term spread and economic growth rates is modelled as a nonlinear one and specifically the logistic smooth transition model is used while a probit model is implemented to forecast recession probabilities specific to this article is the use of the oecd business cycle chronology which was never used before to this end for the italian case overall evidence supports the informative content of the spread in italy over the whole period 1984 2005 although results are more satisfactory as from 1992 in particular recession forecasts are generally better than those obtained with other chronologies previously adopted for the italian case isae and ecri

asymmetric forecast densities for u s macroeconomic variables from a gaussian copula model of cross sectional and serial dependence most existing reduced form macroeconomic multivariate time series models employ elliptical disturbances so that the forecast densities produced are symmetric in this article we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry empirical and skew t distributions are employed for the margins and a high dimensional gaussian copula is used to jointly capture cross sectional and multivariate serial dependence the copula parameter matrix is given by the correlation matrix of a latent stationary and markov vector autoregression var we show that the likelihood can be evaluated efficiently using the unique partial correlations and estimate the copula using bayesian methods we examine the forecasting performance of the model for four u s macroeconomic variables between 1975 q1 and 2011 q2 using quarterly real time data we find that the point and density forecasts from the copula model are competitive with those from a bayesian

price density forecasts in the u s hog markets composite procedures we develop and evaluate quarterly out of sample individual and composite density forecasts for u s hog prices individual density forecasts are generated using time series models and the implied distributions of usda and iowa state university outlook forecasts composite density forecasts are constructed using linear and logarithmic combinations of the individual forecasts and several weighting schemes density forecasts are evaluated on predictive accuracy sharpness goodness of fit calibration and their economic value in a hedging simulation logarithmic combinations using equal and mean square error weights outperform all individual density forecasts and are modestly better than linear composites comparison of the outlook forecasts to the best composite demonstrates the usefulness of the composite procedure and identifies the economic value that more accurate expected price probability distributions can provide to producers

further evidence on the asymmetric behavior of economic time series over the business cycle evidence has recently been presented by salih neftci to support the hypothesis that recessions in economic activity tend to be steeper and more short lived than recoveries in economic activity that evidence however was confined to the behavior of the unemployment rate in the united states in this paper it is shown that when neftci s methods are applied to analyze the behavior of real gross national product investment and productivity in the united states or when they are used to analyze industrial production abroad the asymmetry hypothesis seems to be less compelling

are there asymmetries in uk consumption a time series analysis in this paper we use time series techniques in order to test for asymmetric dynamics in uk consumption the notion that fluctuation over the business cycle are asymmetric has been put forward at various times in the last century nevertheless the most common representations of aggregate time series in macroeconomies are usually smooth and sluggish the use of time series methods should be considered as only the first stage of an empirical investigation of asymmetries it is also essential to develop economic models of asymmetric behaviour and to employ tests of asymmetric adjustment at the level structural realtionship

u s and canadian industrial production indices as coupled oscillators abstract this paper uses ozaki s 1985 variable amplitude coefficient model to explore the impact of different types of dynamical linkages coupling between the indices of industrial production for the u s and canada empirical analysis reveals that for each country the requisite lag structure extends for up to six years and that the coupling linkages are functions of lagged changes in growth rates incorporating these linkages leads to an increased degree of oscillation in the equilibrium paths a marginal improvement in stability and somewhat greater synchronization between the two series the out of sample forecasts for each series are improved by the coupling

real time density forecasts from bayesian vector autoregressions with stochastic volatility central banks and other forecasters are increasingly interested in various aspects of density forecasts however recent sharp changes in macroeconomic volatility including the great moderation and the more recent sharp rise in volatility associated with increased variation in energy prices and the deep global recession pose significant challenges to density forecasting accordingly this paper examines with real time data density forecasts of u s gdp growth unemployment inflation and the federal funds rate from bayesian vector autoregression bvar models with stochastic volatility the results indicate that adding stochastic volatility to bvars materially improves the real time accuracy of density forecasts this article has supplementary material online

the influence factors on choice behavior regarding green products based on the theory of consumption values abstract this study applies the theory of consumption values to determine the influence factors on consumer choice behavior regarding green products and examines whether there are significant differences in consumption values and choice behavior between consumers with different outlooks on environmental concerns one way analysis of variance and multiple regression is used to assess data collected by a questionnaire survey the results indicate that consumers with high environmental concern support green products more and show greater readiness to choose them this study concludes that the main influence factors on consumer choice behavior regarding green products include psychological benefit desire for knowledge novelty seeking and specific conditions and do not include functional values price and quality this study contributes to preliminary but vital insights in effective promotion of green products

was the recent downturn in us real gdp predictable this article uses a small set of variables real gdp the inflation rate and the short term interest rate and a rich set of models atheoretical time series and theoretical structural linear and nonlinear as well as classical and bayesian models to consider whether we could have predicted the recent downturn of the us real gdp comparing the performance of the models to the benchmark random walk model by root mean square errors the two structural theoretical models especially the nonlinear model perform well on average across all forecast horizons in our ex post out of sample forecasts although at specific forecast horizons certain nonlinear atheoretical models perform the best the nonlinear theoretical model also dominates in our ex ante out of sample forecast of the great recession suggesting that developing forward looking microfounded nonlinear dynamic stochastic general equilibrium models of the economy may prove crucial in forecasting turning points

do long swings in the business cycle lead to strong persistence in output abstract this paper investigates how the occasional long swing in the business cycle can produce long memory behavior in us output to prove this theoretical relationship we extend the hamilton markov chain regime switching model of real aggregate output to include the occasional long regime we do this by modeling the duration length of the expansion and recession regimes as draws from a fat tailed distribution with realized durations that are high in variability and occasionally extreme in value empirically we find that the tail indices for the length of us economic booms and busts correspond with the long memory parameter estimates of diebold and rudebusch 1989 long memory and persistence in aggregate output journal of monetary economics 24 189 209 and sowell 1992a modeling long run behavior with the fractional arima model journal of monetary economics 29 277 302 for real us output estimates of our extended regime switching model produce better short and long run forecasts of output in comparison to forecasts with a fractionally integrated model furthermore our estimated regime switching model finds us expansions to be fragile during their infancy but become more and more likely to continue after surviving the first seven quarters

treatment of don t know responses in contingent valuation surveys a random valuation model abstract this paper provides a utility theoretic interpretation of don t know dk responses in contingent valuation surveys using a referendum elicitation procedure the random valuation model in this paper assumes that each respondent of a contingent valuation survey has an implicit valuation distribution rather than a single true value as traditionally assumed in his her mind if an offered referendum bid is not clearly different from the mean value of one s valuation distribution the respondent may give a dk answer to the cv referendum question based on this model a maximum likelihood procedure is proposed for estimating respondents willingness to pay for a nonmarket good with referendum contingent valuation data which include dk responses an empirical illustration of this estimation procedure is also provided

a floor and ceiling model of us output abstract building on previous nonlinear time series models we further examine the form of nonlinearity in us output we develop a model of us output that allows for floor and ceiling effects to alter the dynamics of output growth the model estimated on post korean war quarterly data displays features similar to nonlinear trade cycle models of the 1940s and 1950s thus as predicted by many of the earlier theoretical models our empirical results suggest that the turning points of the business cycle provide new initial conditions for the ensuing growth process we also find important asymmetries in the responses of output to positive and negative shocks this history and shock dependence property is not present in linear or approximately linear models of the type that arise in the standard implementations of real business cycle theory

source of monetary growth uncertainty and economic activity the time varying parameter model a large body of research suggests that uncertainty is an important factor affecting economic activity most earlier research however fails to consider the possibility that uncertainty may affect the value of new information and economic activity differently depending upon its source the author first examines the importance of these different sources for modeling u s monetary growth uncertainty he then empirically relates different sources of monetary growth uncertainty to economic activity measured by real gnp the results suggest that different sources of uncertainty have different impacts on economic activity the results tend to confirm predictions arising in the literature on irreversible investment and uncertainty copyright 1993 by mit press

macroeconomic forecasting and structural change the aim of this paper is to assess whether explicitly modeling structural change increases the accuracy of macroeconomic forecasts we produce real time out of sample forecasts for inflation the unemployment rate and the interest rate using a time varying coefficients var with stochastic volatility tv var for the us the model generates accurate predictions for the three variables in particular for inflation the tv var outperforms in terms of mean square forecast error all the competing models fixed coefficients vars time varying ars and the na ove random walk model these results are also shown to hold over the period commonly referred to as the great moderation

evaluating the bank of england density forecasts of inflation we consider evaluating the uk monetary policy committee s inflation density forecasts using probability integral transform goodness of fit tests these tests evaluate the whole forecast density we also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated where the ranges are chosen to be those of particular relevance to the mpc given its remit of maintaining inflation rates in a band around per annum finally we discuss the decision based approach to forecast evaluation in relation to the mpc forecasts

a nonlinear approach to us gnp a univariate nonlinear model is estimated for us gnp that on many criteria outperforms standard linear models the estimated model is of the threshold autoregressive type and contains evidence of asymmetric effects of shocks over the business cycle in particular the nonlinear model suggests that the post 1945 us economy is significantly more stable than the pre 1945 us economy

short term gdp forecasting with a mixed frequency dynamic factor model with stochastic volatility in this article we develop a mixed frequency dynamic factor model in which the disturbances of both the latent common factor and of the idiosyncratic components have time varying stochastic volatilities we use the model to investigate business cycle dynamics in the euro area and present three sets of empirical results first we evaluate the impact of macroeconomic releases on point and density forecast accuracy and on the width of forecast intervals second we show how our setup allows to make a probabilistic assessment of the contribution of releases to forecast revisions third we examine point and density out of sample forecast accuracy we find that introducing stochastic volatility in the model contributes to an improvement in both point and density forecast accuracy supplementary materials for this article are available online

a study on the implementation of renewable heating technologies in the domestic sector in ireland with implications on consumers decision making abstract the paper critically reviews and explores the impact of renewable energy heat policies to induce technological change in ireland it is in response to the challenge of better understanding the broad effects and attributes of renewable energy policy instruments in ireland and beyond using the irish residential sector as a case study and analysing data of more than 31 600 technology installations under the irish government s greener homes scheme ghs the paper assesses the extent to which policy makers may be informed of the willingness of consumers to adopt these technologies in their homes in doing so it attempts to provide valuable guidance for policy evaluation in relation to renewable energy in the residential sector it represents investment decisions and technological choice by the end user and reflects the growing concern among energy policy markets regarding the representation of user preferences the overall intent is to investigate the implications of analysing different variables and their contribution to making more balanced renewable energy policies it provides a critical analysis of the greener homes scheme the key instrument for implementing ireland s renewable heating policy from 2006 to 2010 established to induce technological change within the residential sector in assessing the impact of the scheme attention focuses on decision frameworks for technological choice and the treatment of market and behavioural failures it considers how consumers have responded to new technological policies aimed at deploying renewable heat technologies and the specific policies aimed at advancing certain technologies over others through a case study investigation the paper explores the relationship and dependencies that influence consumers decision making regarding the choice of renewable energy heating technologies in the domestic sector in ireland consumer preferences and their subsequent investment decisions motives and technological choice are reflected it concludes that while economic factors are important a much broader variety of determinants is required when analysing the process of adoption of technology

real time inflation forecasting in a changing world this article revisits the accuracy of inflation forecasting using activity and expectations variables we apply bayesian model averaging across different regression specifications selected from a set of potential predictors that includes lagged values of inflation a host of real activity data term structure data relative price data and surveys in this model average we can entertain different channels of structural instability by either incorporating stochastic breaks in the regression parameters of each individual specification within this average or allowing for breaks in the error variance of the overall model average or both thus our framework simultaneously addresses structural change and model uncertainty that would unavoidably affect any inflation forecast model the different versions of our framework are used to model u s personal consumption expenditures pce deflator and gross domestic product gdp deflator inflation rates for the 1960 2011 period a real time inflation forecast

bayes estimates of markov trends in possibly cointegrated series stylized facts show that average growth rates of u s per capita consumption and income differ in recession and expansion periods because a linear combination of such series does not have to be a constant mean process standard cointegration analysis between the variables to examine the permanent income hypothesis may not be valid to model the changing growth rates in both series we introduce a multivariate markov trend model that accounts for different growth rates in consumption and income during expansions and recessions and across variables within both regimes the deviations from the multivariate markov trend are modeled by a vector autoregression var model bayes estimates of this model are obtained using markov chain monte carlo methods the empirical results suggest the existence of a cointegration relation between u s per capita disposable income and consumption after correction for a multivariate markov trend this result is also obtained when per capita investment is added to the var

a comparison of linear forecasting models and neural networks an application to euro inflation and euro divisia linear models reach their limitations in applications with nonlinearities in the data in this paper new empirical evidence is provided on the relative euro inflation forecasting performance of linear and non linear models the well established and widely used univariate arima and multivariate var models are used as linear forecasting models whereas neural networks nn are used as non linear forecasting models it is endeavoured to keep the level of subjectivity in the nn building process to a minimum in an attempt to exploit the full potentials of the nn it is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow divisia relative to the traditional simple sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework results obtained suggest that non linear models provide better within sample and out of sample forecasts and linear models are simply a subset of them the divisia index also outperforms the simple sum index when evaluated in a non linear framework 2005 taylor francis group ltd

euromind d a density estimate of monthly gross domestic product for the euro area euromind d is a density estimate of monthly gross domestic product gdp constructed according to a bottom up approach pooling the density estimates of eleven gdp components by output and expenditure type the components density estimates are obtained from a medium size dynamic factor model of a set of coincident time series handling mixed frequencies of observation and ragged edged data structures they reflect both parameter and filtering uncertainty and are obtained by implementing a bootstrap algorithm for simulating from the distribution of the maximum likelihood estimators of the model parameters and conditional simulation filters for simulating from the predictive distribution of gdp both algorithms process sequentially the data as they become available in real time the gdp density estimates for the output and expenditure approach are combined using alternative weighting schemes and evaluated with different tests based on the probability integral transform and by applying scoring rules

asymmetries and nonlinearities in italian macroeconomic fluctuations this paper reports the results of an empirical investigation of business cycle asymmetries in the italian economy macroeconomic time series both annual post unity and quarterly post world war ii are subjected to nonlinearity and asymmetry tests the dynamics of recessions and expansions are then modelled with threshold autoregressive and markov switching models the paper shows that allowing for two regimes is sufficient to account for the finding of neglected nonlinearity the results indicate that business cycle asymmetries can provide both an intuitive economic interpretation and a parsimonious representation of nonlinearities in macroeconomic time series

long memory and persistence in aggregate output abstract we examine persistence in u s aggregate output by estimating fractionally integrated arima models these models provide better low frequency approximations to the wold representation than previous stochastic specifications and earlier results on the importance of a permanent component emerge as special cases we find evidence of long memory which induces persistence though this long memory need not be associated with a unit root our point estimates indicate that macroeconomic shocks while persistent are distinctly less persistent than many earlier studies suggest however confidence intervals associated with the long run response are quite wide

markov switching models and the unit root hypothesis in real us gdp abstract i find that real us gdp is better characterized as a trend stationary markov switching process than as having a regime dependent unit root i examine the effects of both assumptions on the analysis of business cycle features and their implications for the persistence of the dynamic response of output to a random disturbance

are business cycles asymmetric a correction neftci 1984 proposed a nonparametric test procedure for determining whether business cycles are asymmetric in the sense that contractions are steeper than expansions he found evidence of this type of asymmetry in postwar quarterly u s unemployment variables this comment identifies a probable error in neftci s empirical work that reverses the significance of his results for the unemployment rate and it suggests that this test may have low power and be sensitive to measurement error

macroeconomic forecasting performance under alternative specifications of time varying volatility summary this paper compares alternative models of time varying volatility on the basis of the accuracy of real time point and density forecasts of key macroeconomic time series for the usa we consider bayesian autoregressive and vector autoregressive models that incorporate some form of time varying volatility precisely random walk stochastic volatility stochastic volatility following a stationary ar process stochastic volatility coupled with fat tails garch and mixture of innovation models the results show that the ar and var specifications with conventional stochastic volatility dominate other volatility specifications in terms of point forecasting to some degree and density forecasting to a greater degree copyright 2014 john wiley sons ltd

review of barriers to the dissemination of decentralized renewable energy systems abstract this paper reviews the available literature dealing with the barriers to the dissemination of decentralized renewable energy systems decentralized renewable energy systems may face a range of technical economic institutional socio cultural and environmental barrier to their dissemination in the paper barriers impeding the dissemination of decentralized renewable energy systems have been identified and assessed in addition appropriate remedial measures and corresponding responsibility centers as reported in the literature have also been discussed inappropriateness of technology unavailability of skilled manpower for maintenance unavailability of spare parts high cost lack of access to credit poor purchasing power and other spending priorities unfair energy pricing lack of information or awareness and lack of adequate training on operation and maintenance of decentralized renewable energy systems are found to be the most critical barriers long term conducive policies appropriate regulatory framework financial incentives capital subsidies and soft loans to users technology and skill development internalization of externalities in the cost of energy withdrawal of subsidies presently being given to fossil fuels development of specialized institutions cooperation with international agencies participation of local community and awareness generation have been recommended for increased dissemination of decentralized renewable energy systems

volatility transmission and volatility impulse response functions in crude oil markets abstract using daily data from july 2005 to february 2011 for wti dubai and brent futures contracts we employ a var bekk model to investigate crude oil markets integration on the second moment we also quantify the size and persistence of these connections through the analysis of volatility impulse response functions virf for two historical shocks namely the 2008 financial crisis and the bp deepwater horizon oil spill we observe that brent and dubai crude are highly responsive to market shocks whereas wti crude shows the least responsiveness of the three benchmarks which creates questions about its predominance as a benchmark crude oil furthermore we fit the density of the virf at different forecast horizons these fitted distributions are asymmetric showing that the probability of observing a large impact of a shock is lower while the probability of a relatively smaller impact is much higher finally we simulate the virf for a given probability of a random shock the virf shows that only a large shock derived from a smaller probability will result in an increase in expected conditional volatilities these results provide useful insights into the volatility transmission mechanism in crude oil markets and their associated risk estimation and may have significant implications for various market participants and regulators

combining forecast densities from vars with uncertain instabilities recursive weight forecast combination is often found to an ineffective method of improving point forecast accuracy in the presence of uncertain instabilities we examine the effectiveness of this strategy for forecast densities using many vector autoregressive var and autoregressive ar models of output growth inflation and interest rates our proposed recursive weight density combination strategy based on the recursive logarithmic score of the forecast densities produces well calibrated predictive densities for us real time data by giving substantial weight to models that allow for structural breaks in contrast equal weight combinations produce poorly calibrated forecast densities for great moderation data copyright 2010 john wiley sons ltd

regime switching in stochastic models of commodity prices an application to an optimal tree harvesting problem abstract this paper investigates whether a regime switching model of stochastic lumber prices is better for the analysis of optimal harvesting problems in forestry than a more traditional single regime model prices of lumber derivatives are used to calibrate a regime switching model with each of two regimes characterized by a different mean reverting process a single regime mean reverting process is also calibrated the value of a representative stand of trees and optimal harvesting prices are determined by specifying a hamilton jacobi bellman variational inequality which is solved for both pricing models using a implicit finite difference approach the regime switching model is found to more closely match the behavior of futures prices than the single regime model in addition analysis of a tree harvesting problem indicates significant differences in terms of land value and optimal harvest thresholds between the regime switching and single regime models

are output fluctuations transitory according to the conventional view of the business cycle fluctuations in output represent temporary deviations from trend the purpose of this paper is to question this conventional view if fluctuations in output are dominated by temporary deviations from the natural rate of output then an unexpected change in output today should not substantially change one s forecast of output in say five or ten years our examination of quarterly postwar united states data leads us to be skeptical about this implication the data suggest that an unexpected change in real gnp of 1 percent should change one s forecast by over 1 percent over a long horizon

us consumers willingness to pay for green electricity abstract we analyze us consumers demand for environmental attributes of deregulated residential electricity services using results from a survey designed to elicit consumers willingness to pay for such attributes and using results from a hedonic analysis of actual price premiums charged for green electricity in several deregulated markets survey results suggest that many population segments are willing to pay for decreased air emissions even if there is no alteration in fuel source furthermore several groups are willing to pay significantly more when emissions reductions stem from increased reliance upon renewable fuels the hedonic analysis suggests that several product features not considered in the survey help explain real price premiums including fuel mix from newly created renewable generation capacity green e certification brand name and state of offer while survey and hedonic results are not easily compared due to limitations of the survey both point to similar values for key environmental attributes though the survey results are likely to overstate actual willingness to pay in sum the results suggest that consumer driven purchases can in part support the future of renewable generation capacity in the united states though reliance upon other policy alternatives may be needed if energy prices spike

is consumption too smooth for thirty years it has been accepted that consumption is smooth because permanent income is smoother than measured income this paper considers the evidence for the contrary position that permanent income is in fact less smooth than measured income so that the smoothness of consumption cannot be straightforwardly explained by permanent income theory the paper argues that in postwar u s quarterly data consumption is smooth because it responds with a lag to changes in income

unobservables in consumer choice residential energy and the demand for comfort a model of consumption of residential energy in dwellings is developed distinguishing between attributes of housing that provide direct benefits to consumers and attributes that serve as inputs in the production of final goods for example the thermal comfort of dwellings empirical estimates are made of the mode based upon the annual housing survey and the results are used to calculate the effects of changes in energy prices on the consumption of housing residential energy and other goods the analysis suggests that the adjustment process within the housing market permits a great deal of substitution in response to energy price changes copyright 1989 by mit press

are economic time series asymmetric over the business cycle it has long been argued that major cyclical variables such as the unemployment rate display an asymmetric behavior over various phases of the business cycle the paper provides a statistical test for this hypothesis using the framework of finite state markov processes i implement a test to see if the behavior of the unemployment rate is characterized by sudden jumps and slower drops it is argued that the framework provided in the paper can also be used to test other sample path properties of economic time series

characterizing nonlinearities in business cycles using smooth transition autoregressive models during the past few years investigators have found evidence indicating that various time series representing business cycles such as production and unemployment may be nonlinear in this paper it is assumed that if the time series is nonlinear then it can be adequately described by a smooth transition autoregressive star model the paper describes the application of these models to quarterly logarithmic production indices for 13 countries and europe tests reject linearity for most of these series and estimated star models indicate that the nonlinearity is needed mainly to describe the responses of production to large negative shocks such as oil price shocks

do recessions permanently change output abstract this paper examines whether negative innovations to gnp are more or less persistent than positive innovations we find that once we allow for the impulse response of gnp to be asymmetric negative innovations to gnp are observed to be much less persistent than positive ones in particular the effect of a recession on the forecast of output is found to be negligible after only eight to twelve quarters while the effect of a positive shock is estimated to be persistent and amplified over time our results may therefore help reconcile two antagonistic views about the nature of business cycle fluctuations

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

asymmetry in business fluctuations international evidence on friedman s plucking model abstract friedman s plucking model of business fluctuations suggests that output cannot exceed a ceiling level and it is occasionally plucked downward by recession output has depth and steepness this study uses a sample of 12 industrial and emerging economies and finds some evidence that negative shocks are largely transitory while positive shocks are mostly permanent in a few cases as implied by the plucking model output fluctuations tend to be asymmetric recessions are transitory and duration dependent although expansions are not there is however serial correlation in almost all cases international evidence on friedman s plucking model is far from robust

on the dynamic properties of asymmetric models of real gnp there is now a substantial body of evidence that suggests business cycles are asymmetric however the evidence has been accumulated using a wide array of statistical techniques and consequently is based on various definitions of asymmetry this paper examines several parametric models that have been used to study asymmetries in real gnp although these models capture asymmetries in very different ways their dynamic properties are remarkably similar

a model of carbon price interactions with macroeconomic and energy dynamics abstract this paper develops a model of carbon pricing by considering two fundamental drivers of european union allowances economic activity and energy prices on the one hand economic activity is proxied by aggregated industrial production in the eu 27 as it provides the best performance in a preliminary forecasting exercise vs other indicators on the other hand brent natural gas and coal prices are selected as being the main carbon price drivers as highlighted by previous literature the interactions between the macroeconomic and energy spheres are captured in a markov switching var model with two states that is able to reproduce the boom bust business cycle hamilton 1989 first industrial production is found to impact positively negatively the carbon market during periods of economic expansion recession thereby confirming the existence of a link between the macroeconomy and the price of carbon second the brent price is confirmed to be the leader in price formation among energy markets bachmeier and griffin 2006 as it impacts other variables through the structure of the markov switching model taken together these results uncover new interactions between the recently created eu emissions market and the pre existing macroeconomic energy environment

analysis of consumer choice for low carbon technologies by using neural networks abstract through a modelling based contribution this paper critically reviews and explores the impact of low carbon heat policies to induce technological policy development the paper interrogates an irish government funded sustainable energy financed scheme the greener homes scheme launched in 2006 and aimed at the deployment of low carbon technology in the residential sector this paper analyses 31 560 technology installations supported under this scheme and it utilises artificial neural network modelling as a method of better analysing and understanding the effects relationships and dependencies that influence consumer decision making and responses to new technological policies it is responding to a perceived limited understanding of the variables that influence a wider adoption of low carbon technologies and the opportunities and potential that could result in a wider appreciation of the broader impact of market barriers it builds up on the artificial neural networks modelling work explores its application in pattern recognition and interprets its influence in predicting customer behaviour the paper provides an enhanced understanding of the various factors that influence consumer selection of one low carbon technology over another evaluation of the results revealed that the developed artificial neural network model generic 7 6 4 neurons layered architecture is the most appropriate tool and suitable network in predicting indices based on certain social conditions on the choice of certain low carbon technologies

willingness to pay for energy saving measures in residential buildings this paper uses a choice experiment to evaluate the consumers willingness to pay for energy saving measures in switzerland s residential buildings these measures include air renewal ventilation systems and insulation of windows and facades two groups of respondents consisting respectively of 163 apartment tenants and 142 house owners were asked to choose between their housing status quo and each one of the several hypothetical situations with different attributes and prices the estimation method is based on a fixed effects logit model the results suggest that the benefits of the energy saving attributes are significantly valued by the consumers these benefits include both individual energy savings and environmental benefits as well as comfort benefits namely thermal comfort air quality and noise protection

the asymmetric business cycle abstract the business cycle is a fundamental yet elusive concept in macroeconomics in this paper we consider the problem of measuring the business cycle first we argue for the output gap view that the business cycle corresponds to transitory deviations in economic activity away from a permanent or trend level then we investigate the extent to which a general model based approach to estimating trend and cycle for the u s economy leads to measures of the business cycle that reflect models versus the data we find empirical support for a nonlinear time series model that produces a business cycle measure with an asymmetric shape across nber expansion and recession phases specifically this business cycle measure suggests that recessions are periods of relatively large and negative transitory fluctuations in output however several close competitors to the nonlinear model produce business cycle measures of widely differing shapes and magnitudes given this model based uncertainty we construct a mode

flexible inflation targeting and financial stability is it enough to stabilize inflation and output abstract we investigate empirically whether a central bank can promote financial stability by stabilizing inflation and output and whether additional stabilization of asset prices and credit growth would enhance financial stability in particular we employ an econometric model of the norwegian economy to investigate the performance of simple interest rate rules that allow a response to asset prices and credit growth in addition to inflation and output we find that output stabilization tends to improve financial stability additional stabilization of house prices equity prices and or credit growth enhances stability in both inflation and output but has mixed effects on financial stability in general financial stability as measured by e g asset price volatility improves while financial stability measured by indicators that depend directly on interest rates deteriorates mainly because of higher interest rate volatility owing to a more active monetary policy

econometric modeling of regional electricity spot prices in the australian market abstract wholesale electricity markets are increasingly integrated via high voltage interconnectors and inter regional trade in electricity is growing to model this we consider a spatial equilibrium model of price formation where constraints on inter regional flows result in three distinct equilibria in prices we use this to motivate an econometric model for the distribution of observed electricity spot prices that captures many of their unique empirical characteristics the econometric model features supply and inter regional trade cost functions which are estimated using bayesian monotonic regression smoothing methodology a copula multivariate time series model is employed to capture additional dependence both cross sectional and serial in regional prices the marginal distributions are nonparametric with means given by the regression means the model has the advantage of preserving the heavy right hand tail in the predictive densities of price we fit the model to half hourly spot price data in the five interconnected regions of the australian national electricity market the fitted model is then used to measure how both supply and price shocks in one region are transmitted to the distribution of prices in all regions in subsequent periods finally to validate our econometric model we show that prices forecast using the proposed model compares favorably with those from some benchmark alternatives

threshold nonlinearities in output some international evidence the empirical adequacy of linear ar and nonlinear setar models of trend stationary and difference stationary representations of output for canada germany japan the uk and the us are appraised test results suggest the presence of linear model residual structure of some form for all series and nonlinearities of specifically threshold form in trend stationary data for canada germany japan and the us and difference stationary data for germany japan and the us with the exception of canada estimated threshold nonlinear models imply asymmetric dynamics are able to account for all nonlinear structure in the data on the basis of bds statistics and provide sizeable reductions in residual variance in several cases most notably for germany

resource extraction with a carbon tax and regime switching prices exercising your options this paper develops a model of a profit maximizing firm with the option to exploit a non renewable resource choosing the timing and pace of development the resource price is modelled as a regime switching process which is calibrated to oil futures prices a hamilton jacobi bellman equation is specified that describes the profit maximization decision of the firm the model is applied to a problem of optimal investment in a typical oils sands in situ operation and solved for critical levels of oil prices that would motivate a firm to make the large scale investment needed for oil sands extraction as well as to operate mothball or abandon the facility regime shifts can have an important effect on the optimal timing of investment and extraction the paper examines the effect of several carbon tax schemes on optimal timing of construction production and abandonment a form of green paradox is identified

the hamilton model with a general autoregressive component estimation and comparison with other models of economic time series abstract this paper generalizes the hamilton model to the important case in which the autoregressive component need not contain a unit root using u s quarterly real gnp data the model is estimated and the results are compared to those of hamilton some monte carlo evidence for the model is presented and its in sample forecasting performance is discussed and compared to the original hamilton model the arima model and the deterministic time trend model

model averaging in economics an overview standard practice in empirical research is based on two steps first researchers select a model from the space of all possible models second they proceed as if the selected model had generated the data therefore uncertainty in the model selection step is typically ignored alternatively model averaging accounts for this model uncertainty in this paper i review the literature on model averaging with special emphasis on its applications to economics finally as an empirical illustration i consider model averaging to examine the deterrent effect of capital punishment across states in the usa

an empirical characterization of the dynamic effects of police spending on violent and property crime the study estimates the dynamic effects of shocks to police expenditures on measures of violent and property crime rates using annual u s state level data for the period 1960 2015 we employ a structural panel var model and achieve identification by imposing the restriction that police spending responds to structural shocks to crime with at least a lag of 1 year results indicate that a shock to police spending leads to a persistent and significant decreases in violent and property crime rates and b significant and persistent negative impacts on crime rates in periods of high crime but little impacts in periods of low crime variance decompositions show that shocks to police spending account for moderate to large proportions of the variability of u s state level crime rates our findings are robust across separate measures of violent and property crime rates as well as to the inclusion of additional variables to the baseline panel var model jel k42

measuring business cycle time the business cycle analysis of arthur f burns and wesley c mitchell and the national bureau of economic research presumed that aggregate economic variables evolve on a time scale defined by business cycle turning points rather than by months or quarters do macroeconomic variables appear to evolve on an economic rather than a calendar time scale evidence presented here suggests that they do however the estimated economic time scales are only weakly related to business cycle time scales providing evidence against the view underlying traditional business cycle analysis copyright 1987 by university of chicago press

forecasting substantial data revisions in the presence of model uncertainty a recent revision to the preliminary measurement of gdp e growth for 2003q2 caused considerable press attention provoked a public enquiry and prompted a number of reforms to uk statistical reporting procedures in this article we compute the probability of substantial revisions that are greater in absolute value than the controversial 2003 revision the predictive densities are derived from bayesian model averaging over a wide set of forecasting models including linear structural break and regime switching models with and without heteroscedasticity ignoring the nonlinearities and model uncertainty yields misleading predictives and obscures recent improvements in the quality of preliminary uk macroeconomic measurements

is the us business cycle asymmetric some further evidence evidence of nonlinearity in growth rates of monthly industrial production unit labour costs consumer prices and unemployment is reported and alternative representations of that nonlinearity exami

forecasting the distribution of economic variables in a data rich environment this article investigates the relevance of considering a large number of macroeconomic indicators to forecast the complete distribution of a variable the baseline time series model is a semiparametric specification based on the quantile autoregressive qar model that assumes that the quantiles depend on the lagged values of the variable we then augment the time series model with macroeconomic information from a large dataset by including principal components or a subset of variables selected by lasso we forecast the distribution of the h month growth rate for four economic variables from 1975 to 2011 and evaluate the forecast accuracy relative to a stochastic volatility model using the quantile score the results for the output and employment measures indicate that the multivariate models outperform the time series forecasts in particular at long horizons and in tails of the distribution while for the inflation variables the improved performance occurs mostly at the 6 month horizon we also illustra

constructing optimal density forecasts from point forecast combinations summary decision makers often observe point forecasts of the same variable computed for instance by commercial banks imf and the world bank but the econometric models used by such institutions are frequently unknown this paper shows how to use the information available on point forecasts to compute optimal density forecasts our idea builds upon the combination of point forecasts under general loss functions and unknown forecast error distributions we use real time data to forecast the density of us inflation the results indicate that the proposed method materially improves the real time accuracy of density forecasts vis a vis those from the unknown individual econometric models copyright 2013 john wiley sons ltd

mean reversion in equilibrium asset prices this paper demonstrates that negative serial correlation in long horizon stock returns is consistent with an equilibrium model of asset pricing when investors display only a moderate desire to smooth their consumption commonly used measures of mean reversion in stock prices calculated from historical returns data nearly always lie within a 60 percent confidence interval of the median of the monte carlo distributions implied by the authors equilibrium model from this evidence the authors conclude that the degree of serial correlation in the data could plausibly have been generated by their model copyright 1990 by american economic association

a nonparametric investigation of duration dependence in the american business cycle does the termination probability of a business expansion or contraction increase with age this question may be formally addressed by analyzing the nature of duration dependence in aggregate economic activity our null hypothesis is that there is no duration dependence which we test via intentionally nonparametric procedures we also argue that common notion of business cycle periodicity can be usefully interpreted in terms of whole cycle duration dependence we find some evidence for duration dependence in whole cycles and in prewar expansions but little evidence elsewhere

can non linear time series models generate us business cycle asymmetric shape abstract fifteen univariate non linear time series models of us output are evaluated by their ability to reproduce the asymmetric shape of the us business cycle two models account for the growth being faster after a trough and slower before a peak

is investment time irreversible some empirical evidence for disaggregated uk manufacturing data it has long been suggested that investment may be time irreversible and consideration of the option value of waiting to invest has aroused renewed interest in this issue this study tests for time irreversibility in uk investment according to disaggregation by type of investment expenditure and across manufacturing sector groupings the test results reported indicate that the irreversibility of investment patterns varies not only from industry to industry but also according to the type of capital being purchased with significant time irreversibility detected in gross fixed capital formation and aggregate vehicles expenditure and industrial sector groupings comprising fuels and oil refining engineering and vehicles and textiles and leather however only in the first and last of these series is time irreversibility attributable to non linearities in the underlying data generating process and consistent with threshold effects which may be associated with s s type models of investment dynamics

new index of coincident indicators a multivariate markov switching factor model approach abstract this paper extends the univariate markov switching unobserved component model to the multivariate markov switching factor model of coincident economic indicators an approximate ml method is developed to estimate the model the extracted markov switching factor may be interpreted as the coincident index and is comparable to the stock watson index which differs only by the markov switching component using four constituent series of the doc coincident index for the period january 1960 to june 1992 the proposed model generates recessionary and expansionary periods which are remarkably consistent with the nber chronology of the business cycles from the noisy monthly data this paper also finds that duration dependence does matter

business cycle asymmetry a deeper look this paper distinguishes two types of asymmetry in business cycles deepness and steepness deepness is defined as the characteristic that troughs are further below trend than peaks are above most previous research has focused exclusively on steepness which refers to cycles in which contractions are steeper than expansions a test for deepness is proposed and applied to u s post war quarterly unemployment real gnp and industrial production evidence of deepness is found for unemployment and industrial production while the evidence for real gnp is weaker previous evidence of steepness in unemployment is confirmed

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

a monte carlo study of the forecasting performance of empirical setar models in this paper we investigate the multi period forecast performance of a number of empirical selfexciting threshold autoregressive setar models that have been proposed in the literature for modelling exchange rates and gnp amongst other variables we take each of the empirical setar models in turn as the dgp to ensure that the non linearity characterises the future and compare the forecast performance of setar and linear autoregressive models on a number of quantitative and qualitative criteria our results indicate that non linear models have an edge in certain states of nature but not in others and that this can be highlighted by evaluating forecasts conditional upon the regime

business cycle asymmetries characterisation and testing based on markov switching autoregressions tests for business cycle asymmetries are developed for markov switching autoregressive models the tests of deepness steepness and sharpness are wald statistics which have standard asymptotics for the standard two regime model of expansions and contractions deepness is shown to imply sharpness and vice versa whereas the process is always nonsteep two and three state models of u s gnp growth are used to illustrate the approach along with models of u s investment and consumption growth the robustness of the tests to model misspecification and the effects of regime dependent heteroscedasticity are investigated

real time prediction with u k monetary aggregates in the presence of model uncertainty a popular account for the demise of the u k s monetary targeting regime in the 1980s blames the fluctuating predictive relationships between broad money and inflation and real output growth yet ex post policy analysis based on heavily revised data suggests no fluctuations in the predictive content of money in this paper we investigate the predictive relationships for inflation and output growth using both real time and heavily revised data we consider a large set of recursively estimated vector autoregressive var and vector error correction models vecm these models differ in terms of lag length and the number of cointegrating relationships we use bayesian model averaging bma to demonstrate that real time monetary policymakers faced considerable model uncertainty the in sample predictive content of money fluctuated during the 1980s as a result of data revisions in the presence of model uncertainty this feature is only apparent with real time data as heavily revised data obscure these fluctua