ten little treasures of game theory and ten intuitive contradictions this paper reports laboratory data for games that are played only once these games span the standard categories static and dynamic games with complete and incomplete information for each game the treasure is a treatment in which behavior conforms nicely to predictions of the nash equilibrium or relevant refinement in each case however a change in the payoff structure produces a large inconsistency between theoretical predictions and observed behavior these contradictions are generally consistent with simple intuition based on the interaction of payoff asymmetries and noisy introspection about others decisions

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

why has u s inflation become harder to forecast we examine whether the u s rate of price inflation has become harder to forecast and to the extent that it has what changes in the inflation process have made it so the main finding is that the univariate inflation process is well described by an unobserved component trend cycle model with stochastic volatility or equivalently an integrated moving average process with time varying parameters this model explains a variety of recent univariate inflation forecasting puzzles and begins to explain some multivariate inflation forecasting puzzles as well

one two three infinity newspaper and lab beauty contest experiments beauty contest is a game in which participants have to choose typically a number in 0 100 the winner being the person whose number is closest to a proportion of the average of all chosen numbers we describe and analyze beauty contest experiments run in newspapers in uk spain and germany and find stable patterns of behavior across them despite the uncontrollability of these experiments these results are then compared with lab experiments involving undergraduates and game theorists as subjects in what must be one of the largest empirical corroborations of interactive behavior ever tried we claim that all observed behavior across a wide variety of treatments and subject pools can be interpretedas iterative reasoning level 1 reasoning level 2 reasoning and level 3 reasoning are commonly observed in all the samples while the equilibrium choice level maximum reasoning is only prominently chosen by newspaper readers and theorists the results show the empirical power of experiments run with large subject pools and open the door for more experimental work performed on the rich platform offered by newspapers and magazines

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

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

sources procedures and microeconomic effects of innovation fabio arcangeli paul david frank engelman christopher freeman massimo moggi richard nelson luigi orsenigo nathan rosenberg michele salvati g n von tunzelman two anonymous referees and the participants at the meeting of the committee on distribution growth and technical progress of the italian national research council cnr rome november 16 1985 have helped with various redraftings a particularly grateful acknowledgment is for the insightful and patient help of moses abramovitz this work has been undertaken at the science policy research unit spru university of sussex as part of the research program of the designated research centre sponsored by the economic and social research council esrc earlier support to the research that led to this paper by the italian national research council cnr is also gratefully acknowledged the statistical research has been undertaken with the assistance of stephano brioschi ilaria fornari and giovannu prennushi

level k mechanism design non equilibrium models of choice e g level k reasoning have significantly different sometimes more accurate predictions in games than does nash equilibrium when it comes to the maximal set of functions that are implementable in mechanism design however they turn out to have similar implications focusing on single valued rules we discuss the role and implications of different behavioural anchors arbitrary level 0 play and prove a level k revelation principle if a function is level k implementable given any level 0 play it must obey a slight weakening of standard strict incentive constraints further the same condition is also sufficient for level k implementability although the role of specific level 0 anchors is more controversial for the sufficiency argument nonetheless our results provide tight characterizations of level k implementable functions under a variety of level 0 play including truthful uniform and atomless anchors

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

a composite indicator of a firm s innovativeness an empirical analysis based on survey data for swiss manufacturing abstract most empirical studies on innovative activity are based on a single or a very small number of indicator s a procedure not appropriate in view of the complexity of the innovation process therefore in a perspective of ranking firms or industries according to their innovation intensity we develop a composite measure of a firm s innovativeness by using factor analysis of a whole set of innovation variables the resulting aggregate indicator is based on the extraction of two factors depicting the technical and the market dimension in the case of product innovations for new production techniques the two factors refer to the input and output side of the generation of innovations the overall measure is superior to any single innovation variable as shown by canonical correlations which make use of an empirically validated model of innovation behaviour the composite indicator yields economically plausible results at the firm e g innovation patterns and industry levels e g sensible similarities and differences of ranking according to the aggregate measure and r d intensity respectively provided similar indicators and methods are used for several countries a composite indicator may be useful for international comparisons

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

coordination under limited depth of reasoning this paper provides the first unified explanation of behavior in coordinated attack games under both public and private information it demonstrates that the main experimental results such as threshold strategies comparative statics and the differences in behavior under public and private information are robust predictions of limited depth of reasoning models this is in contrast to equilibrium which mispredicts the coordinating roles of public and private information the analysis has implications for understanding macroeconomic phenomena like currency attacks and debt crises which are commonly modeled using incomplete information coordinated attack games

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

international business cycles world region and country specific factors the paper investigates the common dynamic properties of business cycle fluctuations across countries regions and the world we employ a bayesian dynamic latent factor model to estimate common components in macroeconomic aggregates output consumption and investment in a 60 country sample covering seven regions of the world the results indicate that a common world factor is an important source of volatility for aggregates in most countries providing evidence for a world business cycle we find that region specific factors play only a minor role in explaining fluctuations in economic activity we also document similarities and differences across regions countries and aggregates jel f41 e32 c11 c32

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

the voyage of the beagle into innovation explorations on heterogeneity selection and sectors the aim of the paper is to assess heterogeneity of the innovation process using exploratory factor analysis on micro data from the third community innovation survey in 13 countries we identify four patterns that can be interpreted as research user external and production ingredients of innovation all too often it is assumed that how firm innovate can be represented by differences across sectors and or countries to put this proposition under scrutiny we partition variability of the factors scores into components identified by these higher levels sectors and countries matter to a certain extent but far more of the variance is given by heterogeneity among firms within both of them however groups of firms produced by cluster analysis account for much higher share of the variance which indicates that the most relevant stratification of the data cuts across the established sectoral and national boundaries we discuss implications of these findings for understanding of selection in evolutionary economics and for the literature on innovation systems

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

anomalous behavior in a traveler s dilemma the notion of a nash equilibrium has joined supply and demand as one of the two or three techniques that economists instinctively try to use first in the analysis of economic interactions moreover the nash equilibrium and closely related game theoretic concepts are being widely applied in other social sciences and even in biology where evolutionary stability often selects a subset of the nash equilibria many people are uneasy about the stark predictions of the nash equilibrium in some contexts where the extreme rationality assumptions seem implausible kaushik basu s 1994 traveler s dilemma is a particularly convincing example of a case where the unrelenting logic of game theory is at odds with intuitive notions about human behavior the story associated with the dilemma is that two travelers purchase identical antiques while on a tropical vacation their luggage is lost on the return trip and the airline asks them to make independent claims for compensation in anticipation of excessive claims the airline representative announces

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

lying for strategic advantage rational and boundedly rational misrepresentation of intentions starting from hendricks and mcafee s 2000 example of the allies decision to feint at calais and attack at normandy on d day this paper models misrepresentation of intentions to competitors or enemies allowing for the possibility of bounded strategic rationality and rational players responses to it yields a sensible account of lying via costless noiseless messages in many cases the model has generically unique pure strategy sequential equilibria in which rational players exploit boundedly rational players but are not themselves fooled in others the model has generically essentially unique mixed strategy sequential equilibria in which rational players strategies protect all players from exploitation

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

revealed preference rational inattention and costly information acquisition we develop a revealed preference test for optimal acquisition of costly information the test encompasses models of rational inattention sequential signal processing and search we provide limits on the extent to which attention costs can be recovered from choice data we experimentally elicit state dependent stochastic choice data of the form the tests require in simple cases tests con rm that subjects adjust their attention in response to incentives as the theory dictates

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

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

cooperation in the finitely repeated prisoner s dilemma more than half a century after the first experiment on the finitely repeated prisoner s dilemma evidence on whether cooperation decreases with experience as suggested by backward induction remains inconclusive this paper provides a meta analysis of prior experimental research and reports the results of a new experiment to elucidate how cooperation varies with the environment in this canonical game we describe forces that affect initial play formation of cooperation and unraveling breakdown of cooperation first contrary to the backward induction prediction the parameters of the repeated game have a significant effect on initial cooperation we identify how these parameters impact the value of cooperation as captured by the size of the basin of attraction of always defect to account for an important part of this effect second despite these initial differences the evolution of behavior is consistent with the unraveling logic of backward induction for all parameter combinations importantly despite the seemingly contradictory results across studies this paper establishes a systematic pattern of behavior subjects converge to use threshold strategies that conditionally cooperate until a threshold round and conditional on establishing cooperation the first defection round moves earlier with experience simulation results generated from a learning model estimated at the subject level provide insights into the long term dynamics and the forces that slow down the unraveling of cooperation

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

evaluating the joint efficiency of german trade forecasts a nonparametric multivariate approach i analyse the joint efficiency of export and import forecasts by leading economic research institutes for the years 1970 to 2017 for germany in a multivariate setting to this end i compute in a

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

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

endogenous depth of reasoning we introduce a model of strategic thinking in games of initial response unlike standard models of strategic thinking in this framework the player s depth of reasoning is endogenously determined and it can be disentangled from his beliefs over his opponent s cognitive bound in our approach individuals act as if they follow a cost benet analysis the depth of reasoning is a function of the player s cognitive abilities and his payos the costs are exogenous and represent the game theoretical sophistication of the player the benet instead is related to the game payos behavior is in turn determined by the individual s depth of reasoning and his beliefs about the reasoning process of the opponent thus in our framework payos not only aect individual choices in the traditional sense but they also shape the cognitive process itself our model delivers testable implications on players chosen actions as incentives and opponents change we then test the model s predictions with an experiment we administer dierent treatments that vary beliefs over payos and opponents as well as beliefs over opponents beliefs the results of this experiment which are not accounted for by current models of reasoning in games strongly support our theory we also show that the predictions of our model are highly consistent both qualitatively and quantitatively with well known unresolved empirical puzzles our approach therefore serves as a novel unifying framework of strategic thinking that allows for predictions across games

the 11 20 money request game a level k reasoning study we study experimentally a new two player game each player requests an amount between 11 and 20 shekels nis he receives the requested amount and if he requests exactly one shekel less than the other player he receives an additional 20 shekels level k reasoning is appealing due to the natural starting point requesting 20 and the straightforward best response operation nevertheless almost all subjects exhibit at most three levels of reasoning using two variants of the game we demonstrate that the depth of reasoning is not increased by enhancing the attractiveness of the level 0 strategy or by reducing the monetary cost of undercutting the other player

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

strategic pricing with rational inattention to quality this paper studies both theoretically and experimentally the pricing strategy of a rm that faces a consumer who is rationally inattentive to product quality sims 2003 in a standard sequential pricing game rational inattention to quality produces two types of mixed strategy perfect bayesian equilibria one where sellers pool at a low price and buyers are fully inattentive to quality and one where there is semi pooling at a high price and buyers are selectively attentive to quality i characterize these

attention in games an experimental study abstract a common assumption in game theory is that players concentrate on one game at a time however in everyday life we play many games and make many decisions at the same time and have to decide how best to divide our limited attention across these settings in this paper we ask how players solve this attention allocation problem we find that players attention is attracted to particular features of the games they play and how much attention a subject gives to a given game depends on the other game that the person is simultaneously attending to