the open economy consequences of u s monetary policy a failure to identify movements in the federal funds rate that are both unpredictable and independent of other determinants of open economy variables may lead to attenuation bias in the estimated effects of u s monetary policy on the exchange rate and foreign variables using a u s monetary policy measure which isolates unpredictable and independent federal funds rate changes we quantify the magnitude of the attenuation bias for the exchange rate and foreign variables the exchange rate appreciation following a monetary contraction is up to 4 times larger than a recursively identified var estimate there is stronger evidence of foreign interest rate pass through the expenditure reducing effects of a u s monetary policy contraction dominate any expenditure switching effects leading to a positive conditional correlation of international outputs and prices we compare our results with those obtained using identification based upon 1 non recursive var restrictions and 2 restrictions derived from high frequency asset price behavior

litigation and settlement in patent infringement cases a patent grants its owner the right to sue intruders that have been identified the patentholder must then supervise the market and react in case of infringement his reaction may be to go to court to settle or to accept entry we investigate how intensive the monitoring effort should be and how it will influence the entry decision in a simultaneous game even if the penalty paid by the infringer in case of a finding of liability is high the patentholder may prefer a settlement to a trial the likelihood of entry may increase with the penalty in sequential games regardless who plays first entry occurs comparatively less often than in the simultaneous game

monetary policy and investment dynamics evidence from disaggregate data we use disaggregated data on the components of private fixed investment pfi to estimate industry level responses of real investment and capital prices to unanticipated monetary policy the response functions derive from a restricted large scale var estimated over 1959 2007 our results point to significant cross sector heterogeneity in the behavior of pfi prices and quantities for assets belonging to the equipment category of fixed investment we find that quantities rather than prices absorb most of the fallout from a policy shock by contrast the price effects tend to be higher and the output effects lower for nonresidential structures

the dynamic eects of monetary policy a structural factor model approach we use the structural factor model proposed by forni giannone lippi and reichlin 2007 to study the eects of monetary policy the advantage with respect to the traditional vector autoregression model is that we can exploit information from a large data set made up of 112 us monthly macroeconomic series monetary policy shocks are identified using a standard recursive scheme in which the impact eects

interpreting the macroeconomic time series facts the effects of monetary policy existing theory and evidence on the effects of monetary policy are reviewed substantial room for disagreement among economists remains new evidence based on multivariate time series studies of several countries is presented while certain patterns in the data consistent with effective monetary policy are strikingly similar across countries others particularly the tendency of interest rate increases to predict high inflation are harder to reconcile with effective monetary policy

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

understanding the deviation of australian policy rate from the taylor rule this investigation aims to explain and quantify the deviations of the australian policy rate set by reserve bank of australia from the taylor rule a three step econometric procedure designed to reflect the data rich environment in which central banks operate is proposed using information for 229 macroeconomic series this procedure can be applied to data for any economy with inflation targeting monetary rule our application with australian data shows that approximately 65 of australia s policy rate deviation from the taylor rule can be explained systematically with international factors and a domestic factor accounting for 41 9 and 22 5 respectively of the total variation in deviation from the rule

the central banker as a risk manager estimating the federal reserve s preferences under greenspan we derive a natural generalization of the taylor rule that links changes in the interest rate to the balance of the risks implied by the dual objective of sustainable economic growth and price stability this monetary policy rule reconciles economic models of expected utility maximization with the risk management approach to central banking within this framework we formally test and reject the standard assumption of quadratic and symmetric preferences in inflation and output that underlies the derivation of the taylor rule our results suggest that fed policy decisions under greenspan were better described in terms of the fed weighing upside and downside risks to their objectives rather than simply responding to the conditional mean of inflation and of the output gap

foreign entry into underwriting services evidence from japan s big bang deregulation we examined the effect of foreign entry into bond market underwriting activity using issue level data from the japanese samurai and euro yen bond markets we found that the fees charged by japanese underwriters were higher on average than those of foreign underwriters but the difference could be explained by conditioning on issue characteristics our results also suggest that bond issuers sorted properly across underwriters as switching across underwriter nationalities would be expected to result in higher fees however the savings enjoyed by firms issuing with foreign underwriters were modest and statistically insignificant while those of firms issuing with japanese underwriters were substantial and statistically significant this result suggests that japanese underwriters priced their services aggressively over the sample period perhaps in an effort to retain or gain market share this conjecture is supported by a matching exercise that examined the liberalization of foreign underwriter access to the samurai bond market using euro yen bond issues as a control foreign entry led to a statistically and economically significant decrease of 16 basis points on average in underwriting fees in the samurai bond market overall our results suggest that the international market for japanese bond underwriting services was partially segmented by nationality as issuers appear to have preferred habitats but that liberalization increased overall market competition

the effects of monetary policy using structural factor analysis the traditional vector autoregression var method is widely used to trace out the effects of monetary policy innovations on the economy however this method suffers from the curse of dimensionality so that in practice vars are estimated on a limited number of variables leading to a potential missing information problem in this article we use the method of structural factor analysis to evaluate the effects of monetary policy on key macroeconomic variables in a data rich environment this methodology allows us to extract information on monetary policy and its impact on the economy from a much larger data set than is possible with the traditional var method we propose two structural factor models one is the structural factor augmented vector autoregressive sfavar model and the other is the structural factor vector autoregressive sfvar model compared to the traditional var both models incorporate information from hundreds of data series series that can be and are monitored by the central bank in

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

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

did financial factors matter during the great recession abstract yes they mattered to reply to this question we assess the predictive content of macroeconomic and financial latent factors on the key variables industrial productivity short term interest rate and inflation during the great recession period 2007 2009 in the united states in this respect we propose a forecasting analysis using a factor augmented var model when we estimate the model with only financial factors we improve the predictions in the short and medium horizons meanwhile when we estimate the model with only macroeconomic factors we improve the forecasting performance in the longer horizon

measuring the effects of dollar appreciation on asia a favar approach abstract exchange rate shocks have mixed effects on economic activity in both theory and empirical var models in this paper we extend the empirical literature by considering the implications of a positive shock to the u s dollar in a factor augmented vector autoregression favar model for the u s and three large asian economies korea japan and china the favar framework allows us to represent a country s aggregate economic activity by a latent factor generated from a broad set of underlying observable economic indicators to control for global conditions we also include in the favar a global conditions index which is another latent factor generated from the economic indicators of major trading partners we find that a dollar appreciation shock reduces economic activity and inflation not only for the u s economy but also for all three asian economies this result which is robust to a number of alternative specifications suggests that in spite of their disparate economic structures and policy regimes the dollar appreciation shock affects the asian economies primarily through its impact on u s aggregate demand and this demand channel dominates the expenditure switching channel that affects a country s export competitiveness

are statistical reporting agencies getting it right data rationality and business cycle asymmetry this article provides new evidence on the rationality of early releases of industrial production ip and producer price index ppi data rather than following the usual practice of examining only first available and fully revised data we examine the entire revision history for each variable thus we are able to assess for example whether earlier releases of data are in any sense less rational than later releases and when data become rational our findings suggest that seasonally unadjusted ip and ppi become rational after approximately 3 4 months whereas seasonally adjusted versions of these series remain irrational for at least 6 12 months after initial release for all variables examined we find evidence that the remaining revision is predictable from its own past or from publicly available information in other economic and financial variables in addition we find a clear increase in the volatility of revisions during recessions suggesting that early data releases are less reliable in toughe

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

monetary policy shocks and foreign investment income evidence from a large bayesian var abstract this paper assesses the transmission of monetary policy in a large bayesian vector autoregression based on the approach proposed by banbura et al 2010 the paper analyzes the impact of monetary policy shocks in the united states and canada not only on a range of domestic aggregates trade flows and exchange rates but also foreign investment income the analysis provides three main results first a surprise monetary policy contraction has a statistically important impact on both gross and net foreign investment income flows in both countries against the background of growing foreign wealth and investment income this result provides preliminary evidence that foreign balance sheet channels might play an increasingly significant role for monetary transmission second the impact of monetary policy on foreign investment income flows differs considerably across asset categories and over time suggesting that the investment instruments and the currency denomination of a country s foreign assets and liabilities are potentially relevant for the way in which monetary policy affects the domestic economy finally the results support existing evidence on the effectiveness of large vector autoregressions and the bayesian shrinkage approach in eliminating price and exchange rate puzzles

principal components at work the empirical analysis of monetary policy with large data sets the empirical analysis of monetary policy requires the construction of instruments for future expected inflation dynamic factor models have been applied rather successfully to inflation forecasting in fact two competing methods have recently been developed to estimate large scale dynamic factor models based respectively on static and dynamic principal components this paper combines the econometric literature on dynamic principal components and the empirical analysis of monetary policy we assess the two competing methods for extracting factors on the basis of their success in instrumenting future expected inflation in the empirical analysis of monetary policy we use two large data sets of macroeconomic variables for the usa and for the euro area our results show that estimated factors do provide a useful parsimonious summary of the information used in designing monetary policy copyright 2005 john wiley sons ltd

international house prices and macroeconomic fluctuations abstract the paper investigates linkages between general macroeconomic conditions and the housing market for the g 7 area among the key results of the paper we find that the us are an important source of global fluctuations not only for real activity nominal variables and stock prices but also for real housing prices secondly albeit distinct driving forces for real activity and financial factors can be pointed out sizeable global interactions are also evident in particular global supply side shocks are an important determinant of g 7 house prices fluctuations the linkage between real housing prices and macroeconomic developments is however bidirectional with investment showing in general a stronger reaction than consumption and output to housing price shocks implications for the real effects of the sub prime crisis are also explored

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