market concentration and competition in eastern europe a key feature of soviet type economies is the excessive concentration of production and the skewed size distribution of enterprises this is the root cause of the soft budget constraint and a natural outcome of the political economy of these countries given entrenched political support for a system which favours producers relative to consumers it will be hard to pursue an active competition policy though it is essential for successful reform we examine a hypothetical restructuring of polish state enterprises and argue that this should be undertaken before they are privatized hungary appears to have started such a process already this abstract was borrowed from another version of this item

dynamic model averaging in large model spaces using dynamic occam s window abstract bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data when data arrive sequentially and the generating model can change over time dynamic model averaging dma extends model averaging to deal with this situation often in macroeconomics however many candidate explanatory variables are available and the number of possible models becomes too large for dma to be applied in its original form we propose a new method for this situation which allows us to perform dma without considering the whole model space but using a subset of models and dynamically optimizing the choice of models at each point in time this yields a dynamic form of occam s window we evaluate the method in the context of the problem of nowcasting gdp in the euro area we find that its forecasting performance compares well with that of other methods

where do we go from here 2 real wages effective demand and economic development a central purpose of this paper is to argue for a more active role for historical analysis in filling out and extending classical theory firstly what is required is a more modern vision of capitalist growth which would not only include such classical variables as the rate of profit and accumulation but also take into account the changing level and composition of the standard of living and how this interrelates with the compositional evolution of the industrial structure including the effect of new technology and changes in industrial organisation such as the development of new industries new products and new systems of marketing the second important need is for a more differentiated class analysis with which to study the growth process this would require a detailed consideration of the historical stratification and re stratification of the working class and would incorporate an analysis of the impact of and the interaction between the evolving industrial and political organisation of labour state policy collective bargaining the restructuring of labour resulting from changing power relations in the market and in the labour process changing technology and industrial organisation these processes have particular relevance in the present context for inter and intra class distribution of income and how this relates to the level and structuring of demand the paper consists of five main sections the first considers representative attempts to incorporate historical processes into theory the second considers the development in the structure of consumption in britain since 1860 the third links changing consumption to the standard of living the fourth examines the relationship between the standard of life and institutional developments in wage determination and in welfare provision and the fifth is a brief attempt to relate these factors to economic development

nowcasting sales growth of manufacturing companies in india abstractthe performance of private corporate sector is used as an important demand indicator for monetary policy making as these data are received with a lag assessing and monitoring of corporate sales on a real time basis poses a significant challenge to policy makers in india in this context this article attempts to nowcast quarterly sales growth of indian manufacturing companies and gdp growth of india using dynamic factor modelling framework a multiple level framework through turning point analysis and elastic net structure is used to overcome the overfitting problem during variable selection empirical results show improvement in forecast accuracy for one quarter ahead nowcast using 3 factor and 4 factor models over the benchmark model however absolute dominance of 3 factor models over 4 factor models was not established as such the article has proposed a forecast combination technique to nowcast sales growth of manufacturing companies in india

tracking the slowdown in long run gdp growth using a dynamic factor model that allows for changes in both the long run growth rate of output and the volatility of business cycles we document a significant decline in long run output growth in the united states our evidence supports the view that most of this slowdown occurred prior to the great recession we show how to use the model to decompose changes in long run growth into its underlying drivers at low frequencies a decline in the growth rate of labor productivity appears to be behind the recent slowdown in gdp growth for both the united states and other advanced economies when applied to real time data the proposed model is capable of detecting shifts in long run growth in a timely and reliable manner

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

exploiting the monthly data flow in structural forecasting a quarterly stochastic general equilibrium dsge model is combined with a now casting model designed to read timely monthly information as it becomes available this implies 1 mapping the structural quarterly dsge with a monthly version that maintains the same economic restrictions 2 augmenting the model with a richer data set and 3 updating the estimates of the dsge s structural shocks in real time following the publication calendar of the data our empirical results show that our methodology enhances the predictive accuracy in now casting an analysis of the great recession also shows that our framework would have helped tracing the dsge s structural shocks in real time obtaining for example a more timely account of the 2008 contraction

competition and corporate governance in transition this paper examines the elements of institutional development critical to the enhancement of company performance in transition economies this includes initial conditions forms of privatization institutional frameworks and the competitiveness of markets comparing empirical evidence the paper concludes that there is a clear distinction in effectiveness of policies followed and their impact between central europe and cis countries this divergence is attributed to fundamentally different political attitudes toward reform the need of cis governments to gain political support for reform and as a consequence of the desire of central european countries to join european union

nowcasting the real time informational content of macroeconomic data abstract a formal method is developed for evaluating the marginal impact that intra monthly data releases have on current quarter forecasts nowcasts of real gross domestic product gdp growth the method can track the real time flow of the type of information monitored by central banks because it can handle large data sets with staggered data release dates each time new data are released the nowcasts are updated on the basis of progressively larger data sets that reflecting the unsynchronized data release dates have a jagged edge across the most recent months

the behaviour of state firms in eastern europe pre privatisation in this paper we explore the behaviour of state firms pre privatisation the incentives and the constraints facing managers and the nature and the power of the coalitions within the firms we show that managers on low incentive payment schemes with little formal stake in privatisation and who face possible redundancy have little incentive to embark on restructuring hardened budget constraints career concerns and potential stakes in the privatised firm however may strengthen managerial incentives to restructure we then introduce an influence function which captures how the distribution of winners and losers within the firm and size of their loss and gain affects the probability of restructuring the function illustrates how strong opposition coming from large concentrated losses is likely to dominate diffuse support from small widely distributed gains government measures such as hardening budget constraints financing of severance payments and selective debt writedowns affect the distribution of gainers and losers and may be used to overcome blocking coalitions and increase support for restructuring examination of a range of enterprise case studies vindicates our hypothesis that the structure of control and production strongly affect incentives to restructure centralised management structures the presence of non performing units and a functional division of activities have all acted as serious constraints on the unbundling restructuring process whilst the removal of state subsidies has been critical in forcing firms to rationalise production and unbundle activities

forecasting the world economy in the short term 1433 audrone jakaitiene and stephane dees forecasting the world economy is a difficult task given the complex interrelationships within and across countries this paper proposes a number of approaches to forecast short term changes in selected world economic variables and aims first at ranking various forecasting methods in terms of forecast accuracy and second at checking whether methods forecasting directly aggregate variables direct approaches outperform methods based on the aggregation of country specific forecasts bottom up approaches overall all methods perform better than a simple benchmark for short horizons up to 3 months ahead among the forecasting approaches used factor models appear to perform the best moreover direct approaches outperform bottom up ones for real variables but not for prices finally when country specific forecasts are adjusted to match direct forecasts at the aggregate levels top down approaches the forecast accuracy is neither improved nor deteriorated i e top down and bottom up approaches are broadly equivalent in terms of country specific forecast accuracy

nowcasting global economic growth a factor augmented mixed frequency approach assessing accurately global economic conditions is a great challenge for economists the international monetary fund proposes within its periodic world economic outlook report a measure of the global gdp annual growth that is generally considered as the benchmark nowcast by macroeconomists in this paper we put forward an alternative approach to provide monthly nowcasts of the annual global growth rate our approach builds on a factor augmented mixed data sampling fa midas model that enables i to account for a large monthly database including various countries and sectors of the global economy and ii to nowcast a low frequency macroeconomic variable using higher frequency information pseudo real time results over the period 2010 16 show that this approach provides reliable and timely nowcasts of the world gdp annual growth on a monthly basis

dynamic hierarchical factor models this paper uses multilevel factor models to characterize within and between block variations as well as idiosyncratic noise in large dynamic panels block level shocks are distinguished from genuinely common shocks and the estimated block level factors are easy to interpret the framework achieves dimension reduction and yet explicitly allows for heterogeneity between blocks the model is estimated using an mcmc algorithm that takes into account the hierarchical structure of the factors the importance of block level variations is illustrated in a four level model estimated on a panel of 445 series related to different categories of real activity in the united states

mixed frequency var models with markov switching dynamics this paper extends the markov switching vector autoregressive models to accommodate both the typical lack of synchronicity that characterizes the real time daily flow of macroeconomic information and economic indicators sampled at different frequencies the results of the empirical application suggest that the model is able to capture the features of the nber business cycle chronology very accurately

monthly pass through ratios abstract this paper estimates monthly pass through ratios from import prices to consumer prices in real time conventional time series methods impose restrictions to generate exogenous shocks on exchange rates or import prices when estimating pass through coefficients instead our estimation strategy follows an event study approach based on monthly releases in import prices projections from a dynamic common factor model with daily panels before and after monthly releases of import prices define the innovation for import prices we apply our identification procedure to swiss prices and find strong evidence that the median of the monthly pass through ratio is around 0 3 tests show that standard assumptions of non real time data and limited information breath are critical for the pass through estimates

targeted export promotion with several oligopolistic industries abstract we study export promotion policies in situations where several oligopolistic industries compete for the services of a sector specific factor of production the partial equilibrium argument for strategic subsidies must be modified to incorporate general equilibrium effects working through the factor market we find that these effects generally weaken the case for profit shifting subsidies in a benchmark case with symmetric exporting industries fixed coefficients technologies and an inelastic supply of the specific factor free trade is shown to be optimal

forecasting the gdp of a small open developing economy an application of favar models gdp forecasting remains a challenge for a small open developing economy faced with insufficient and low frequency data central bank forecasters cannot project gdp reliably for the purpose of mone

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

gdp nowcasting application and constraints in a small open developing economy despite data limitations an attempt is made to find out if a gdp nowcasting model can provide reliable forecasts for a small open economy two competing bayesian vector autoregressive models are tested rigorously to obtain the optimal model by minimizing in sample forecasting errors the main finding of this study is that gdp nowcasting can produce reliable results for a small open economy despite the unavailability of sufficient data sets and the lack of high frequency indicators

from theory into practice restructuring and dynamism in transition economies this paper draws on microeconomic industry level and macroeconomic evidence to investigate the mecha nisms of enterprise restructuring in transition economies its outcomes in terms of industry level export perform ance and its interaction with macroeconomic policy and constraints the aim is to throw light on the process by which catch up is taking place in the leading transition economies we begin at the micro level and find that institutional changes have produced improvements in performance more or less in line with theoretical predic tions variation in the extent ofpolicy changes helps to account for cross country differences in restructuring behaviour in the leading transition countries where growth has been under way for a number of years many features of the enterprise sector differentiate it from that of an advanced market economy to measure the extent of catch up associated with the reforms use is made of detailed information about the quality of goods traded on the eu market in the final section the inclusion of macroeconomic constraints allows distinctive transition paths to catching up in the visegrad countries to be identified

predictability of output growth and inflation a multi horizon survey approach we develop an unobserved components approach to study surveys of forecasts containing multiple forecast horizons under the assumption that forecasters optimally update their beliefs about past current and future state variables as new information arrives we use our model to extract information on the degree of predictability of the state variable and the importance of measurement errors in the observables empirical estimates of the model are obtained using survey forecasts of annual gdp growth and inflation in the united states with forecast horizons ranging from 1 to 24 months and the model is found to closely match the joint realization of forecast errors at different horizons our empirical results suggest that professional forecasters face severe measurement error problems for gdp growth in real time while this is much less of a problem for inflation moreover inflation exhibits greater persistence and thus is predictable at longer horizons than gdp growth and the persistent component of bot

does ownership always matter abstract the objective of this paper is to explain and illustrate the complex relationship between ownership arrangements and enterprise performance it is commonly argued that efficiency will be lower in the public sector than the private because enterprise objectives deviate from maximisation of profits and because monitoring arrangements are inadequate due to the absence of capital market discipline we argue that public ownership does make the owner manager relationship more complicated because the chain of principals and agents is expanded objectives are politically determined and these are conveyed by a policy making administrative structure to management but the relative efficiency of public as against private ownership actually depends on the efficacy of capital market monitoring on the political and constitutional system on the information and sanctions available to policy makers and on the nature of the management market variation in these factors can help to explain the different natures and roles of the public sector between countries

forecasting consumption the role of consumer confidence in real time with many predictors summary we study the role of consumer confidence in forecasting real personal consumption expenditure and contribute to the extant literature in three substantive ways first we re examine existing empirical models of consumption and consumer confidence not only at the quarterly frequency but using monthly data as well second we employ real time data in addition to commonly used revised vintages third we investigate the role of consumer confidence in a rich information context we produce forecasts of consumption expenditures with and without consumer confidence measures using a dynamic factor model and a large real time jagged edge dataset in a robust way we establish the important role of confidence surveys in improving the accuracy of consumption forecasts manifesting primarily through the services component during the recession of 2007 2009 sentiment is found to have a more pervasive effect on all components of aggregate consumption durables non durables and services copyright 2015 john wiley sons ltd

u s monetary policy surprises identification with shifts and rotations in the term structure we develop a model to extract measures of monetary policy surprises from the maturity structure of the yield curve the model endogenously allows for the fact that the yield curve may either shift or rotate in response to monetary policy shocks a latent factor model approach with identification through heteroskedasticity harnesses the term structure to extract monetary policy shocks the approach offers informational advantages over event studies results from the u s term structure from 1994 strongly support the hypothesis that differing term structure responses are reactions to different types of monetary policy shock rather than differing reactions to the same policy shock

estimating time variation in measurement error from data revisions an application to backcasting and forecasting in dynamic models over time economic statistics are refined this implies that data measuring recent economic events are typically less reliable than older data such time variation in measurement error affects optimal forecasts measurement error and its time variation are of course unobserved our contribution is to show how estimates of these can be recovered from the variance of revisions to data using a behavioural model of the statistics agency we illustrate the gains in forecasting performance from exploiting these estimates using a real time dataset on uk aggregate expenditure data copyright 2009 john wiley sons ltd

automated earnings forecasts beat analysts or combine and conquer prior studies attribute analysts forecast superiority over time series forecasting models to their access to a large set of firm industry and macroeconomic information an information advantage which they use to update their forecasts on a daily weekly or monthly basis a timing advantage this study leverages recently developed mixed data sampling midas regression methods to synthesize a broad spectrum of high frequency data to construct forecasts of firm level earnings we compare the accuracy of these forecasts to those of analysts at short horizons of one quarter or less we find that our midas forecasts are more accurate and have forecast errors that are smaller than analysts when forecast dispersion is high and when the firm size is smaller in addition we find that combining our midas forecasts with analysts forecasts systematically outperforms analysts alone which indicates that our midas models provide information orthogonal to analysts our results provide preliminary support for th

forecasting oil prices high frequency financial data are indeed useful abstract the paper examines the importance of combining high frequency financial information along with the oil market fundamentals in order to gain incremental forecasting accuracy for oil prices inspired by french et al 1987 and bollerslev et al 1988 who maintain that future asset returns are also influenced by past volatility we use daily volatilities and returns from financial and commodity markets to generate real out of sample forecasts for the monthly oil futures prices our results convincingly show that although the oil market fundamentals are useful for long run forecasting horizons the combination of the latter with high frequency financial data significantly improve oil price forecasts by reducing the rmse of the no change forecast by approximately 68 results are even more impressive during the oil price collapse period of 2014 15 these findings suggest that we cannot ignore the information extracted from the financial markets when forecasting oil prices our results are both statistically and economically significant as suggested by several robustness tests

directly unproductive profit seeking dup activities this paper propses directly unproductive profit seeking dup activities as a general concept that embraces a wide range of recently analyzed economic activities including the subset of rent seeking activities considered by krueger it then proceeds to provide a synthesis and generalization of the welfare theoretic analysis of such activities by developing a fourfold categorization of cases depending on the levels of distortions before and after the dup activity thus a unification and overview of the subject are achieved

why do forecasters disagree lessons from the term structure of cross sectional dispersion abstract key sources of disagreement among economic forecasters are identified by using data on cross sectional dispersion in forecasters long and short run predictions of macroeconomic variables dispersion among forecasters is highest at long horizons where private information is of limited value and lower at short forecast horizons moreover differences in views persist through time such differences in opinion cannot be explained by differences in information sets our results indicate they stem from heterogeneity in priors or models differences in opinion move countercyclically with heterogeneity being strongest during recessions where forecasters appear to place greater weight on their prior beliefs

neo liberalism and new labour policy economic performance historical comparisons and future prospects the paper analyses19760 70s inflation the replacement of keynesian with neo liberal economic policy and the post 1979 decline in inflation it is shown that the fall in inflation is explained by trends in import prices rather than by switches in economic policy however new labour s conversion to neo liberalism means that no alternative to it is on political offer despite returns to pre keynesian policy making the success of which will depend on price policies based on an understanding of the institutional roots of inflation

facts and challenges from the great recession for forecasting and macroeconomic modeling this paper provides a survey of business cycle facts updated to take account of recent data emphasis is given to the great recession which was unlike most other postwar recessions in the united states in being driven by deleveraging and financial market factors we document how recessions with financial market origins are different from those driven by supply or monetary policy shocks this helps explain why economic models and predictors that work well at some times do poorly at other times we discuss challenges for forecasters and empirical researchers in light of the updated business cycle facts

words are the new numbers a newsy coincident index of the business cycle i construct a daily business cycle index based on quarterly gdp growth and textual information contained in a daily business newspaper the newspaper data are decomposed into time series representi

real time data and fiscal policy analysis a survey of the literature abstractthis paper surveys the empirical research on scal policy analysis based on real timedata this literature can be broadly divided in three groups that focus on 1 the statisticalproperties of revisions in scal data 2 the political and institutional determinants of scaldata revisions and of one year ahead projection errors by governments and 3 the reactionof scal policies to the business cycle it emerges that rst scal data revisions are largeand initial releases are biased estimates of nal values second the presence of strong scalrules and institutions leads to relatively more accurate releases of scal data and smalldeviations of scal outcomes from government plans third the cyclical stance of scalpolicies is estimated to be more counter cyclical when real time data are used instead ofex post data finally more work is needed for the development of real time datasets for scalpolicy analysis in particular a comprehensive real time dataset including scal variablesfor industrialized and possibly developing countries published and maintained by centralbanks or other institutions is still missing

have standard vars remained stable since the crisis small or medium scale vars are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism this requires the var parameters to be stable over the evaluation and forecast sample or to explicitly consider parameter time variation the earlier literature focused on whether there were sizable parameter changes in the early 1980s in either the conditional mean or variance parameters and in the subsequent period till the beginning of the new century in this paper we conduct a similar analysis but focus on the effects of the recent crisis using a range of techniques we provide substantial evidence against parameter stability the evolution of the unemployment rate seems particularly different relative to its past behavior we then discuss and evaluate alternative methods to handle parameter instability in a forecasting context while none of the methods clearly emerges as best some techniques turn out to be useful to improve the forecasting performance

up the average cost curve inefficient entry and the new protectionism abstract a two country model is developed in which each country produces one good with increasing returns the goods being perfect or imperfect substitutes with cournot nash behavior and free entry certain restrictive trade policies have effects opposite to their favorable effect under noentry assumptions import tariffs and export subsidies lead to inefficient entry that raises rather than decreases the average production cost of and price charge by the domestic industry with negative welfare consequences we argue that these predictions of our model are closely consistent with extensive canadian data on entry exit and firms responses to trade liberalization

tourism and economic development a survey this article surveys the literature on tourism and economic development identifying the contribution that tourism can make to development including foreign currency income and employment and the costs that it entails single equation and system of equations models for estimating tourism demand are provided indicating developing countries potential to benefit from increasing expenditure on tourism but their susceptibility to deterioration in price competitiveness the main sectors of tourism supply transportation tour operators travel agents and accommodation are examined and the importance of cross country integration between firms is highlighted the article argues that many of the problems associated with the use of environmental resources for tourism stem from market failure and it considers methods for increasing sustainably the returns from them

the yield spread puzzle and the information content of spf forecasts while the yield spread has long been recognized as a good predictor of recessions it seems to have been largely overlooked by professional forecasters we examine this puzzle established by rudebusch and williams 2009 in a data rich environment including not just the yield spread but many other predictors as well we confirm the puzzle in this context by examining the contributions of both the spf forecasts and the yield spread in predicting recessions and by examining the information content of spf forecasts directly furthermore we take the first step towards a possible resolution of this puzzle by recognizing the heterogeneity across professional forecasters

when does privatization work the impact of private ownership on corporate performance in the transition economies this paper compares the performance of privatized and state firms in the transition economies of central europe while controlling for various forms of selection bias it argues that privatization has different effects depending on the types of owners to whom it gives control in particular privatization to outsider but not insider owners has significant performance effects where privatization is effective the effect on revenue performance is very pronounced but there is no comparable effect on cost reduction overlooking the strong revenue effect of privatization to outsider owners leads to a substantial overstatement of potential employment losses from postprivatization restructuring

combining judgment and models this paper proposes a parsimonious and model consistent method for combining forecasts generated by structural microfounded models and judgmental forecasts the method delivers along several dimensions first it improves the forecasting performance of the model second it allows interpreting the judgmental forecasts through the lens of the model finally it provides a framework to assess the informational content of the judgmental forecasters i illustrate the proposed methodology with a real time forecasting exercise using a simple neo keynesian dynamic stochastic general equilibrium model and the survey of professional forecasters 2010 the ohio state university

are daily financial data useful for forecasting gdp evidence from mexico this article evaluates the use of financial data sampled at high frequencies to improve short term forecasts of quarterly gdp for mexico the model uses both quarterly and daily sampling frequencies while remaining parsimonious in particular the mixed data sampling midas regression model is employed to deal with the multi frequency problem to preserve parsimony factor analysis and forecast combination techniques are used to summarize the information contained in a data set containing 392 daily financial series our findings suggest that the midas model incorporating daily financial data leads to improvements in quarterly forecasts of gdp growth over traditional models that either rely only on quarterly macroeconomic data or average daily frequency data the evidence suggests that this methodology improves the forecasts for the mexican gdp notwithstanding its higher volatility relative to that of developed countries furthermore we explore the ability of the midas model to provide forecast updates for gdp growth nowcasting

wages economic development and the customary standard of life this paper examines empirically the evolution of the customary standard of life and how this relates to real wages and economic development its starting point is sraffa s reintroduction of the classical notion of wages as the cost of reproducing labour so that they are necessarily a charge on production however when considering a production system generating a surplus sraffa offered no explanation of how the surplus might be realised and distributed rather he concentrated on the choice of technique as the profit share varied from 0 to 1 his approach was one of taking a snapshot of a productive system at a point in time in contrast this paper explores the trend in wages in the uk over the past 150 years and the evolving level and composition of what became the social necessities of worker consumption i e the customary standard of life in this process four dynamically interacting processes can be identified i a progressive increase in the productive potential of the system ii the diffusion of a greater quantity and varieties of consumer goods the growth of property ownership by consumers and their use of credit in a cumulative improvement in their customary standard of life iii the consolidation of the customary standard of life into real wages by collective bargaining and iv diffusion of improved living standards by an extension of collective bargaining coverage to include groups previously excluded and the growth of the welfare state in which the failure to achieve the customary standard of life defines poverty and triggers policy designed to alleviate it the central role played by the customary standard of life in driving real wages means that the inputs of labour power into commodity production can be represented by the commodity composition of the customary standard of life in sraffa style analyses in this the successive cross sections in the historical flow of economic development showing the commodity flows into and out of production will be ever changing like the still frames in a moving picture show moreover such a historical approach rules out the possibility that at any time changes in the rate of profit will precipitate the switching of methods of production past choices of techniques are historically embedded in the capital stock the composition of which is modified by new investment and the scrapping of old as it wears out becomes technically outmoded and or demand for its products declines nevertheless changes in the distribution of income have consequences for the future path of economic and social development and what this might be is arguably the most useful area for economic and social research copyright oxford university press

forecasting core inflation the case of south africa forecasting and estimating core inflation has recently gained attention especially for inflation targeting countries following research showing that targeting headline inflation may not be optimal a central bank can miss the signal due to the noise despite its importance there is sparse literature on estimating and forecasting core inflation in south africa with the focus still on measuring core inflation this paper emphasises predicting core inflation using large time varying parameter vector autoregressive models tvp vars factor augmented var and structural break models using quarterly data from 1981q1 to 2013q4 we use mean squared forecast errors msfe and predictive likelihoods to evaluate the forecasts in general we find that i small tvp vars consistently outperform all other models ii models where the errors are heteroscedastic do better than models with homoscedastic errors iii models assuming that the forgetting factor remains 0 99 throughout the forecast period outperforms models that allow for the forgetting factors to change with time and iv allowing for structural break does not improve the predictability of core inflation overall our results imply that additional information on the growth rate of the economy and interest rate is sufficient to forecast core inflation accurately but the relationship between these three variables needs to be modelled in a time varying nonlinear fashion

markov switching midas models this article introduces a new regression model markov switching mixed data sampling ms midas that incorporates regime changes in the parameters of the mixed data sampling midas models and allows for the use of mixed frequency data in markov switching models after a discussion of estimation and inference for ms midas and a small sample simulation based evaluation the ms midas model is applied to the prediction of the u s economic activity in terms of both quantitative forecasts of the aggregate economic activity and the prediction of the business cycle regimes both simulation and empirical results indicate that ms midas is a very useful specification

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

euro area business cycles in turbulent times convergence or decoupling we study the business cycle properties of the four largest european economies in the wake of the recent recession episodes the analysis is based on the factors estimated from a multi country and multi sector data rich environment we measure alikeness of business cycles by studying the synchronization of up and down phases the convergence properties of country fluctuations towards the euro area ea cycles and the contribution of the ea factor to national gdp volatilities while the economic fluctuations of the four ea member states were similar before the global financial turmoil we gather compelling evidence of an asymmetric behaviour of spanish fluctuations relative to the ea one

short term forecasting with mixed frequency data a midasso approach abstractin this article we extend the targeted regressor approach suggested in bai and ng 2008 for variables sampled at the same frequency to mixed frequency data our midasso approach is a combination of the unrestricted mixed frequency data sampling approach u midas see foroni et al 2015 castle et al 2009 bec and mogliani 2013 and the lasso type penalized regression used in bai and ng 2008 called the elastic net zou and hastie 2005 we illustrate our approach by forecasting the quarterly real gdp growth rate in switzerland

factor augmented varma models with macroeconomic applications we study the relationship between vector autoregressive moving average varma and factor representations of a vector stochastic process we observe that in general vector time series and factors cannot both follow finite order var models instead a var factor dynamics induces a varma process while a var process entails varma factors we propose to combine factor and varma modeling by using factor augmented varma favarma models this approach is applied to forecasting key macroeconomic aggregates using large u s and canadian monthly panels the results show that favarma models yield substantial improvements over standard factor models including precise representations of the effect and transmission of monetary policy

real time forecasting with a mixed frequency var this article develops a vector autoregression var for time series which are observed at mixed frequencies quarterly and monthly the model is cast in state space form and estimated with bayesian methods under a minnesota style prior we show how to evaluate the marginal data density to implement a data driven hyperparameter selection using a real time dataset we evaluate forecasts from the mixed frequency var and compare them to standard quarterly frequency var and to forecasts from midas regressions we document the extent to which information that becomes available within the quarter improves the forecasts in real time this article has online supplementary materials

macroeconomic forecasting using diffusion indexes this article studies forecasting a macroeconomic time series variable using a large number of predictors the predictors are summarized using a small number of indexes constructed by principal component analysis an approximate dynamic factor model serves as the statistical framework for the estimation of the indexes and construction of the forecasts the method is used to construct 6 12 and 24 monthahead forecasts for eight monthly u s macroeconomic time series using 215 predictors in simulated real time from 1970 through 1998 during this sample period these new forecasts outperformed univariate autoregressions small vector autoregressions and leading indicator models

forecasting oil price realized volatility using information channels from other asset classes motivated from ross 1989 who maintains that asset volatilities are synonymous to the information flow we claim that cross market volatility transmission effects are synonymous to cross market information flows or information channels from one market to another based on this assertion we assess whether cross market volatility flows contain important information that can improve the accuracy of oil price realized volatility forecasting we concentrate on realized volatilities derived from the intra day prices of the brent crude oil and four different asset classes stocks forex commodities and macro which represent the different information channels by which oil price volatility is impacted from we employ a har framework and estimate forecasts for 1 day to 66 days ahead our findings provide strong evidence that the use of the different information channels enhances the predictive accuracy of oil price realized volatility at all forecasting horizons numerous forecasting evaluation tests and alternative model specifications confirm the robustness of our results

the effectiveness of non standard monetary policy measures evidence from survey data we assess the perception of professional forecasters regarding the effectiveness of unconventionalmonetary policy measures undertaken by the u s federal reserve after the collapse of lehmanbrothers using individual survey data we analyse the changes in forecasting of bond yields aroundthe announcement and implementation dates of non standard monetary policies the resultsindicate that bond yields are expected to drop significantly for at least one year after theannouncement and the implementation of accommodative policies

divisia monetary aggregates and us gdp nowcasting this article nowcasts us quarterly real gdp growth rate with dynamic factor model dfm using divisia monetary aggregate index divisia m1 m2 m3 and exploits information from a large unbalanced

financial conditions indexes for the united states and euro area abstract financial conditions indexes are developed for the united states and euro area using a wide range of financial indicators and a dynamic factor model the financial conditions indexes are shown to be useful for forecasting economic activity and have good revision properties variants of the indexes that allow for cross economy effects reveal very strong financial linkages across the united states and euro area

is free trade passe abstract if there were an economist s creed it would surely contain the affirmations i understand the principle of comparative advantage and i advocate free trade yet the case for free trade is currently more in doubt than at any time since the 1817 publication of ricardo s principles of political economy and this is due to changes that have recently taken place in the theory of international trade while new developments in international trade theory may not yet be familiar to the profession at large they have been substantial and radical in the last ten years the traditional constant returns perfect competition models of international trade have been supplemented and to some extent supplanted by a new breed of models that emphasizes increasing returns and imperfect competition these new models call into doubt the extent to which actual trade can be explained by comparative advantage they also open the possibility that government intervention in trade via import restrictions export subsidies

nowcasting u s headline and core inflation we propose a new and parsimonious model for nowcasting headline and core inflation in the u s price index for personal consumption expenditures pce and the consumer price index cpi

introducing the euro sting short term indicator of euro area growth we set out a model to compute short term forecasts of the euro area gdp growth in real time to allow for forecast evaluation we construct a real time dataset that changes for each vintage date and includes the exact information that was available at the time of each forecast with this dataset we show that our simple factor model algorithm which uses an easy to replicate methodology is able to forecast the euro area gdp growth as well as professional forecasters who can combine the best forecasting tools with the possibility of incorporating their own judgement in this context we provide examples showing how data revisions and data availability affect point forecasts and forecast uncertainty copyright 2010 john wiley sons ltd