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

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

some empirical evidence on the effects of shocks to monetary policy on exchange rates this paper investigates the effects of shocks to u s monetary policy on exchange rates we consider three measures of these shocks orthogonalized shocks to the federal funds rate orthogonalized shocks to the ratio of nonborrowed to total reserves and changes in the romer and romer index of monetary policy in sharp contrast to the literature we find substantial evidence of a link between monetary policy and exchange rates specifically according to our results a contractionary shock to u s monetary policy leads to i persistent significant appreciations in u s nominal and real exchange rates and ii significant persistent deviations from uncovered interest rate parity in favor of u s interest rates

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

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

the fed and the stock market an identification based on intraday futures data this article develops a new identification procedure to estimate the contemporaneous relation between monetary policy and the stock market within a vector autoregression var framework the approach combines high frequency data from the futures market with the var methodology to circumvent exclusion restrictions and achieve identification our analysis casts doubt on var models imposing a recursive structure between innovations in policy rates and stock returns we find that a tightening in policy rates has a negative impact on stock prices and that the federal reserve fed has responded significantly to movements in the stock market estimates are robust to various model specifications

agricultural productivity and structural transformation evidence from brazil we study the eects of the adoption of new agricultural technologies on structural transfor mation to guide empirical work we present a simple model where the eect of agricultural productivity on industrial development depends on the factor bias of technical change we test the predictions of the model by studying the introduction of genetically engineered soybean seeds in brazil which had heterogeneous eects on agricultural productivity across areas with dierent soil and weather characteristics we nd that technical change in soy production was strongly labor saving and lead to industrial growth as predicted by the model

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

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

monetary policy shifts and the term structure we estimate the effect of shifts in monetary policy using the term structure of interest rates in our no arbitrage model the short rate follows a version of the taylor s 1993 discretion versus policy rules in practice carnegie rochester conference series on public policy 39 195 214 rule where the coefficients on the output gap and inflation vary over time the monetary policy loading on the output gap has averaged around 0 4 and has not changed very much over time the overall response of the yield curve to output gap components is relatively small in contrast the inflation loading has changed substantially over the last 50 years and ranges from close to zero in 2003 to a high of 2 4 in 1983 long term bonds are sensitive to inflation policy shifts with increases in inflation loadings leading to higher short rates and widening yield spreads

ecb monetary policy surprises identification through cojumps in interest rates this paper proposes a new econometric approach to disentangle two distinct response patterns of the yield curve to monetary policy announcements based on cojumps in intraday tick data of a short and long term interest rate we develop a day wise test that detects the occurrence of a significant policy surprise and identifies the market perceived source of the surprise the new test is applied to 133 policy announcements of the european central bank ecb in the period from 2001 2012 our main findings indicate a good predictability of ecb policy decisions and remarkably stable perceptions about the ecb s policy preferences

asset market responses to conventional and unconventional monetary policy shocks in the united states abstract we quantify the responses of a wide range of united states financial market variables to domestic monetary policy shocks over conventional and unconventional monetary policy environments our results show that responses to policy shocks are in the same direction but generally larger and more significant in the unconventional period the larger responses are mostly due to larger shocks in the unconventional period but some variables show evidence of a larger transmission of shocks we separately use our framework to test shadow short rate estimates as a proxy for short maturity interest rates across conventional and unconventional periods

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

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

is corruption grease grit or a gamble corruption increases variance of productivity across countries the effect of corruption on economic growth has attracted interest in empirical development economics the conventional view of corruption as impediment for growth has been challenged by the grease on the wheels hypothesis we take a new perspective on the issue and suggest corruption as macro risk referred to as a gamble hypothesis using cross country data and two alternative indicators of corruption we find corruption to be a significant driver of heteroscedasticity in total productivity this supports the new gamble hypothesis we also note some misleading interpretations in the previously published frontier applications to avoid these shortcomings we apply a flexible semi nonparametric estimator

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

unravelling financial market linkages during crises an empirical model of multiple asset classes across countries is formulated in a latent factor framework a special feature of the model is that financial market linkages during periods of financial crises including spillover and contagion effects are formally specified the model also captures a range of common factors including global shocks country and market shocks and idiosyncratic shocks the framework is applied to modelling linkages between currency and equity markets during the east asian financial crisis of 1997 98 the results provide strong evidence that cross market links are important spillovers have a relatively larger effect on volatility than contagion but both are statistically significant

estimation of a forward looking monetary policy rule a time varying parameter model using ex post data abstract in this paper we consider estimation of a time varying parameter model for a forward looking monetary policy rule by employing ex post data a heckman type 1976 the common structure of statistical models of truncation sample selection and limited dependent variables and a simple estimator for such models annals of economic and social measurement 5 475 492 two step procedure is employed in order to deal with endogeneity in the regressors this allows us to econometrically take into account changing degrees of uncertainty associated with the fed s forecasts of future inflation and gdp gap when estimating the model even though such uncertainty does not enter the model directly we achieve efficiency in estimation by employing the standardized prediction errors for inflation and gdp gap as bias correction terms in the second step regression we note that no other empirical literature on monetary policy deals with this important issue our empirical results also reveal new aspects not found in the literature previously that is the history of the fed s conduct of monetary policy since the early 1970s can in general be divided into three subperiods the 1970s the 1980s and the 1990s the conventional division of the sample into pre volcker and volcker greenspan periods could mislead the empirical assessment of monetary policy

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

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

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

mapping india s regional subcultures implications for international management as india continues to emerge as a global economic player scholars and practitioners increasingly need to understand the cultural heterogeneity within this large and populous nation based on lenartowicz and roth s framework of culture assessment we have identified nine distinct subcultural regions of india and used explanations grounded in functional and neo institutional theories to account for the origin and maintenance of cultural distinctiveness of these regions further we developed seven cultural value dimensions for the indian society and used these to hypothesize and empirically test the existence of cultural differences within india results supported our hypothesized arguments this study advances our knowledge of how global functional and institutional forces have combined with national forces to shape india s overall culture and how more local forces have shaped its regions methodologically it identifies and develops measures that specifically reflect the values of individuals living in india and uses these to assess intra national cultural differences within this nation further it suggests how use of multiple methods can enable us to understand the simultaneous presence of somewhat contradictory values within a society the study also provides applications of the proposed cultural value dimensions and advises implications of regional subcultures for various social and organizational phenomena

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

institutional flaws and corruption incentives in india abstract india has achieved a respectable rate of economic growth in an environment that is quite permissive of corrupt practices to the extent that acts of corruption if sufficiently clever are not scorned but praised despite the coexistence of corruption and unprecedented economic growth we argue that there is unrealised potential for further growth that is held back by the institutions of administration and associated corruption with growth as substantial as it has been there is less pressure on those at the top to restrain corruption there is still significant room for the indian economy to accelerate its growth through steps to reduce corruption particularly as it impacts businesses and individuals in their day to day economic pursuits a simple framework is sketched to describe the transactions that lead to grand systemic and petty or retail corruption the focus of this paper is on the institutions of administration that foster corruption at all levels and the consequences of petty corruption

economic growth size of the agricultural sector and urbanization in africa this paper uses variations in international commodity prices and rainfall to construct instrumental variables estimates of the within country effect that changes in the size of the agricultural sector and gdp per capita growth have on the urbanization rate for a panel of 41 african countries during the period 1960 2007 the paper s three main findings are that i decreases in the share of agricultural value added lead to a significant increase in the urbanization rate ii conditional on changes in the share of agricultural value added gdp per capita growth does not significantly affect the urbanization rate iii increases in the urbanization rate had a significant negative average effect on gdp per capita growth

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

beyond dualism agricultural productivity small towns and structural change in bangladesh this paper uses a framework that goes beyond rural urban dualism and highlights the role of small town economy in understanding structural change in a developing country it provides a theoretical and empirical analysis of the role of agricultural productivity in structural transformation in the labor market the empirical work is based on a general equilibrium model that formalizes the demand and labor market linkages the small town draws labor away from the rural areas to produce goods and services whose demand may depend largely on rural income the theory clarifies the role played by the income elasticity of demand and the wage elasticity with respect to productivity increase in agriculture for productivity growth to lead to a demand effect the wage elasticity has to be lower than a threshold when the demand for goods and services produced in small towns comes mainly from the adjacent rural areas the demand effect can outweigh the negative wage effect and lead to higher employment in the town goods sector using rainfall as an instrument the empirical analysis finds a significant positive effect of agricultural productivity on rice yield and agricultural wages productivity shock increases wages more in the rural sample compared with the small town economy sample but structural change in employment is more pronounced in the small town economy in the rural sample it increases employment only in small scale manufacturing and services in contrast a positive productivity shock has large and positive impacts on employment in construction and transport education health and other services and manufacturing employment in larger scale enterprises located in small towns and cities agricultural productivity growth induces structural transformation within the services sector in small towns with employment in skilled services growing at a faster pace than that of low skilled services

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

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

monetary policy surprises and interest rates evidence from the fed funds futures market abstract this paper estimates the impact of monetary policy actions on bill note and bond yields using data from the futures market for federal funds to separate changes in the target funds rate into anticipated and unanticipated components interest rates response to anticipated target rate changes is small while their response to unanticipated changes is large and highly significant these responses are generally consistent with the expectations hypothesis of the term structure surprise target rate changes have little effect on expectations of future actions however which helps to explain the lack of empirical support for the expectations hypothesis at the short end of the yield curve

the extent of the market and stages of agricultural specialization this paper provides empirical evidence of nonlinearity in the relationship between crop specialization in a village economy and the extent of the market size of the urban market relevant for the village the results suggest that the portfolio of crops in a village economy becomes more diversified initially as the extent of the market increases however after the market size reaches a threshold the production structure becomes specialized again this evidence on the stages of agricultural diversification is consistent with the stages of diversification identified in the recent literature for the economy as a whole and also for the manufacturing sector the evidence highlights the importance of improving farmers access to markets through investment in transport infrastructure and removal of barriers to trading

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

monetary policy and market interest rates this thesis contains four chapters each of which examines different aspects of the uncertainty facing monetary policymakers monetary policy and market interest rates investigates how interest rates set on financial markets respond to policy actions taken by the monetary authorities the reaction of market rates is shown to depend crucially on market participants interpretation of the factors underlying the policy move these theoretical predictions find support in an empirical analysis of the u s financial markets predicting monetary policy using federal funds futures prices examines how prices of federal funds futures contracts can be used to predict policy moves by the federal reserve although the futures prices exhibit systematic variation across trading days and calendar months they are shown to be fairly successful in predicting the federal funds rate target that will prevailafter the next meeting of the federal open market committee from 1994 to 1998 monetary policy with uncertain parameters examines the effects of parameter uncertainty on the optimal monetary policy strategy under certain parameter configurations increasing uncertainty is shown to lead to more aggressive policy in contrast to the accepted wisdom should central banks be more aggressive examines why a certain class of monetary policy models leads to more aggressive policy prescriptions than what is observed in reality these counterfactual results are shown to be due to model restrictions rather than central banks being too cautious in their policy behavior an unrestricted model taking the dynamics of the economy and multiplicative parameter uncertainty into account leads to optimal policy prescriptions which are very close to observed federal reserve behavior

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

when did the fomc begin targeting the federal funds rate what the verbatim transcripts tell us in october 1982 the fomc deemphasized m1 and moved to what is commonly referred to as a borrowed reserves operating procedure sometime thereafter the fomc switched to a funds rate targeting procedure but never formally announced the change given the close correspondence between a borrowed reserves operating procedure and a funds rate targeting procedure thornton 1988 suggested that the fomc went immediately to a funds rate targeting procedure others date the switch to the funds rate procedure later meulendyke 1998 suggests the switch came in late 1987 while others suggest the change occurred later this paper reviews the verbatim transcripts of the fomc meetings to establish the timing of the switch the verbatim transcripts suggest that the fomc effectively switched to a funds rate targeting procedure in 1982 the documentary evidence is supported by an analysis of the spread between the funds rate and the funds rate target which suggests that the differences in the behavior of the spread before october 1979 and after october 1982 are relatively small and economically unimportant

has monetary policy become more effective we investigate the implications of changes in the structure of the u s economy for monetary policy effectiveness estimating a vector autoregression over the pre and post 1980 periods we provide evidence of a reduced effect of monetary policy shocks in the latter period we estimate a structural model that replicates well the economy s response in both periods and perform counterfactual experiments to determine the source of the change in the monetary transmission mechanism and in the economy s volatility we find that by responding more strongly to inflation expectations monetary policy has stabilized the economy more effectively in the post 1980 period

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

has u s monetary policy changed evidence from drifting coefficients and real time data despite the large amount of empirical research on monetary policy rules there is surprisingly little consensus on the nature or even the existence of changes in the conduct of u s monetary policy three issues appear central to this disagreement 1 the specific type of changes in the policy coefficients 2 the treatment of heteroskedasticity and 3 the real time nature of the data used this paper addresses these issues in the context of forwardlooking taylor rules with drifting coefficients the estimation is based on real time data and accounts for the presence of heteroskedasticity in the policy shock the findings suggest important but gradual changes in the rule coefficients not adequately captured by the usual split sample estimation in contrast to orphanides 2002 2003 i find that the fed s response to the real time forecast of inflation was weak in the second half of the 1970s perhaps not satisfying taylor s principle as suggested by clarida gali and gertler 2000 however the response to inflation was strong before 1973 and gradually regained strength from the early 1980s onward moreover as in orphanides 2003 the fed s response to real activity fell substantially and lastingly during the 1970s

identifying vars based on high frequency futures data abstract using the prices of federal funds futures contracts we measure the impact of the surprise component of federal reserve policy decisions on the expected future trajectory of interest rates we show how this information can be used to identify the effects of a monetary policy shock in a standard var this alternative approach to identification is quite different and we argue more plausible than the conventional identifying restrictions we find that a usual recursive identification of the model is rejected as is any identification that insists on a monetary policy shock having an exactly zero effect on prices contemporaneously we nevertheless agree with the conclusion of much of the var literature that only a small fraction of the variance of output can be attributed to monetary policy shocks

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

international monetary policy surprise spillovers abstract this is the first paper to examine international monetary surprise spillovers and to estimate the response of security prices to monetary and nonmonetary surprises monetary surprises have a slope effect on the domestic yield curve short maturity yields adjust much more than longer maturity yields these results are similar to other studies the following results are new us monetary surprises spill over and affect australian yields and equity returns australian monetary surprises do not spill over to the us nonmonetary surprises are much more important than monetary policy surprises in explaining longer maturity yield changes and equity returns

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

were there regime switches in u s monetary policy working paper 2004 14 june 2004 abstract a multivariate model identifying monetary policy and allowing for simultaneity and regime switching in coefficients and variances is confronted with u s data since 1959 the best fit is with a model that allows time variation in structural disturbance variances only among models that also allow for changes in equation coefficients the best fit is for a model that allows coefficients to change only in the monetary policy rule that model allows switching among three main regimes and one rarely and briefly occurring regime the three main regimes correspond roughly to periods when most observers believe that monetary policy actually differed and the differences in policy behavior are substantively interesting though statistically ill determined the estimates imply monetary targeting was central in the early 80s but was also important sporadically in the 70s the changes in regime were essential neither to the rise in inflation in the 70s nor to its decline in the 80s jel classification e52 e47 c53 key words counterfactuals lucas critique policy rule monetary targeting simultaneity volatility model comparison i the debate over monetary policy change in an influential paper clarida gali and gertler 2000 cgg presented evidence that us monetary policy changed between the 1970 s and the 1980 s indeed that in the 70 s it was drastically worse they found that the policy rule apparently followed in the 70 s was one that when embedded in most stochastic general equilibrium models would imply non uniqueness of the equilibrium and hence vulnerability of the economy to sunspot fluctuations of arbitrarily large size their estimated policy rule for the later period on the other hand eliminated this indeterminacy these results are a possible explanation of the volatile and rising inflation of the 70 s and of its subsequent decline the cgg analysis has two important weaknesses one is that it fails to account for stochastic volatility us macroeconomic variables and particularly the federal funds rate have gone through periods of tranquility and of agitation with forecast error variances varying greatly from period to period ignoring such variation does not lead to inconsistent estimates of model parameters when the forecasting equations themselves are constant but it strongly biases toward a finding of changed parameters tests of the stability of the forecasting equations the other weakness is that the cgg analysis rests on powerful and implausible identifying assumptions they require that we accept that the response of the monetary authority to expected future inflation and output does not depend on the recent history of inflation money growth or output it is hard to understand why this should be so especially in the 70 s when monetarism was a prominent theme in policy debates congress was requiring reports from the fed of projected time paths of monetary aggregates and financial markets were reacting sensitively to weekly money supply numbers the requirement for existence and uniqueness of equilibrium in dynamic models is that the monetary policy rule show a more than unit response of interest rates to the sum of the logs of all nominal variables that appear on the right hand side of the reaction function if we force a particular measure of expected future inflation to proxy for all the nominal variables that actually appear independently in the reaction function we are bound to get distorted conclusions on the one hand because expected future inflation will be a noisy measure of the full set of nominal influences on policy we might get downward bias in our estimates from the usual errorsin variables effect on the other hand to the extent that expected future inflation like most expected future values shows less variation than current nominal variables we could find a mistaken scaling up of coefficients

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

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

price scissors and the structure of the economy this paper undertakes three sets of tasks i it analyzes positive and normative aspects of price scissors the domestic terms of trade between agriculture and industry within nonsocialist as well as socialist ldcs the critical role of the economy s institutional features e g external trade environment wage and income determination and wage productivity effects is emphasized certain aspects of the soviet industrialization debate and subsequent collectivization are interpreted ii it develops simple rules to delineate who gains and who loses within agriculture from changes in terms of trade iii it presents powerful and informationally parsimonious rules for pareto improving price reforms for cash crops and agricultural inputs