Two Bayesian sampling schemes are outlined to estimate a K-state Markov switching model with time-varying transition probabilities. The multinomial logit model for the transition probabilities is alternatively expressed as a random utility model and as a difference random utility model. The estimation uses data augmentation and both sampling schemes can be based on Gibbs sampling. Based on the model estimate, we are able to discriminate the model against a smooth transition model, in which the state probability may be influenced by a variable, but without depending on the past prevailing state. Formulating a definition allows to determine the relevant threshold level of the covariate influencing the transition distribution without resorting to the usual grid search. Identification issues are addressed with random permutation sampling. In terms of efficiency the extension to difference random utility in combination with random permutation sampling performs best. To illustrate the method, we estimate a two-pillar Phillips curve for the euro area, in which the inflation rate depends on the low-frequency components of M3 growth, real GDP growth and the change in the government bond yield, and on the highfrequency component of the output gap. Using recent data series, the effect of the low-frequency component of M3 growth depends on regimes determined by lagged credit growth.
In reaction to recent requests for interoperability between central counterparties of European stock markets, regulators have issued new guidelines to contain systemic risk. Our analysis confirms that the currently applied cross-CCP risk management model can be a source of contagion, particularly if applied in multilateral frameworks. While regulators' new guidelines eliminate systemic risk, this comes at the cost of an inefficiently overcollateralised clearing system. We discuss further approaches that contain systemic risk while reducing or eliminating overcollateralisation. Interoperability is of economic importance as it may contribute to the efficiency and safety of a worldwide fragmented clearing infrastructure.
Contrary to the common wisdom that asset prices are hardly possible to forecast, we show that high and low prices of equity shares are largely predictable. We propose to model them using a simple implementation of a fractional vector autoregressive model with error correction (FVECM). This model captures two fundamental patterns of high and low prices: their cointegrating relationship and the long memory of their difference (i.e. the range), which is a measure of realized volatility. Investment strategies based on FVECM predictions of high/low US equity prices as exit/entry signals deliver a superior performance even on a risk-adjusted basis.
We develop a general equilibrium model of vertical innovation in which multiple firms compete monopolistically in the quality space. The model features many firms, each of which holds the monopoly to produce a unique quality level of an otherwise homogenous good, and consumers who are heterogeneous in their valuation of the good's quality. If the marginal cost of production is convex with respect to quality, multiple rms coexist, and their equilibrium markups are determined by the degree of convexity and the density of quality-competition. To endogenize the latter, we nest this industry setup in a Schumpeterian model of endogenous growth. Each firm enters the industry as the technology leader and successively transits through the product cycle as it is superseded by further innovations. The intrinsic reason that innovation happens in our economy is not one of displacing the incumbent; rather, innovation is a means to di-erentiate oneself from existing firms and target new consumers. Aggregate growth arises if, on the one hand, increasingly wealthy consumers are willing to pay for higher quality and, on the other hand, private firms' innovation generates income growth by enlarging the set of available technologies. Because the frequency of innovation determines the toughness of product market competition, in our framework, the relation between growth and competition is reversed compared to the standard Schumpeterian framework. Our setup does not feature business stealing in the sense that already marginal innovations grant non-negligible prots. Rather, innovators sell to a set of consumers that was served relatively poorly by pre-existing firms. Nevertheless, "creative destruction" prevails as new entrants make the set of available goods more di-erentiated, thereby exerting a pro-competitive e-ect on the entire industry.
What is the impact of import competition from low-wage countries (LWCs) on inflationary pressure in Europe? This paper examines whether labor-intensive exports from emerging Europe, Asia, and other global regions have a uniform impact on producer prices in Germany, France, Italy, Sweden, and the United Kingdom. In a panel covering 110 (4-digit) NACE industries from 1995 to 2008, instrumental variable estimations predict that LWC import competition is associated with strong price effects. More specifically, when LWC exporters capture 1% of European market share, producer prices decrease by about 3%. In contrast, no effect is present for import competition from low-wage countries in Central and Eastern Europe. Next, decomposing the mechanisms that underlie the LWC price effect on European industry, we show that import competition has a pronounced effect on average productivity and only a muted effect on wages. Owing to the exit of firms and the increase in productivity, LWC import competition is shown to have substantially reduced employment in the European manufacturing sector.
This paper investigates the speed and completeness of the pass-through from market rates to mortgage rates in Switzerland. The pass-through dynamics are studied under a marginal funding cost perspective. By choosing the appropriate benchmark rates, this study takes into account banks' forecasts of the evolution of their funding costs. It is found that the passthrough of rates of adjustable-rate mortgages is incomplete and sluggish compared to the rates of mortgages with a fixed maturity. For the latter, changes in market rates appear to be transmitted quickly and completely, particularly when benchmark rates are falling. This finding suggests that a low-interest-rate environment stimulates competition among financial institutions. Evidence for a structural change is found for all interest rates. The structural change occurred around the beginning of 2007 for fixed-rate mortgages and in mid-2005 for floating-rate mortgages. For all mortgage rates, asymmetries are detected in the pre-break period. More specifically, the adjustment of fixed-rate-mortgage rates is characterized by downward rigidity, which supports the existence of some form of imperfect competition. By contrast, the rates of adjustable-rate mortgages exhibit upward price stickiness. This result suggests that competition was stronger in this specific mortgage-lending market. In the post-break period, no clear evidence is found in favor of asymmetries with respect to the adjustment coefficient.
This paper disentangles fluctuations in disaggregate prices into macroeconomic and idiosyncratic components using a factor-augmented vector autoregression (FAVAR) in order to shed light on sectoral inflation dynamics in Switzerland. We find that disaggregated prices react only slowly to monetary policy and other macroeconomic shocks, but relatively quickly to idiosyncratic shocks. We document that there is a large heterogeneity across sectors in the reaction to monetary policy shocks and show that sectors with larger volatility of idiosyncratic shocks react more readily to monetary policy. This finding stands in contrast to the rational inattention model of price setting. We also find that sectors, which change prices infrequently, react less strongly but if they do change their prices, they adjust them by a large amount. This suggests that the source of sluggish response to aggregate shocks is heterogeneity in menu costs rather than rational inattention. Furthermore, even though prices respond with a significant delay to identified monetary policy shocks, we find no evidence of a price puzzle on average. For single sectors, however, we still find a hump-shaped response which can partially be explained by the fact that, by law, rents are tied to interest rates in Switzerland.
Central banks have won in credibility as from the mid-eighties by keeping inflation under control. However, confidence in low inflation might have encouraged agents to excessive risk-taking, leading asset prices to rise. Moreover, the belief in a Federal Reserve guarantee against a sharp market decline spread across US markets as from the nineties. This belief, commonly referred to as the Greenspan put, raised again the question about the role of asset prices in monetary policy decisions. The problem is addressed by modeling the reaction of the Fed to stockmarket deviations from fundamentals over the period stretching from August 1987 to October 2008, which corresponds to the periods where Greenspan until January 2006 and Bernanke from thereon were chairmen. A Taylor rule describing the Fed's nominal feedback rule to inflation and economic activity on a monthly basis is extended to take account of asset prices. The indicators considered are deflation and volatility in stock prices. Furthermore, a Markov switching process allows to capture contemporaneous as well as forward-looking monetary policy responses to asset prices over the period. We find out that taking asset price deflation improves the Taylor rule fit by some 8%. In periods when the Fed was actively pursuing an expansive or restrictive monetary policy, its reaction to volatility or deflation of financial markets was significant. We also see that the reaction of the Fed to asset prices was greater during financial crises, especially when modeling a forward-looking decision process. Agents' confidence in a stronger response of the US central bank to significant market declines urging to an easing of monetary conditions in their favour was therefore not unfounded.
To date, various central banks have lacked detailed statistical evidence on developments in the unsecured interbank money market. Furfine (1999) introduced the idea of calculating unsecured overnight interbank lending by using data of a RTGS system. Based on data from the Swiss payment system (SIC) we developed an algorithm to identify unsecured interbank loans in Swiss francs. In contrast to Furfine (1999) we also identify longer-term transactions. We thereby gain a deeper insight on the size and structure of the unsecured interbank money market in Swiss francs. This is the first time that SIC data have been used to identify transactions and market rates in the unsecured Swiss franc money market. Overall, the estimates show that after the collapse of Lehman Brothers loss of confidence led to a freezing-up of the market for several months and a decrease in daily turnover.
Using 10 years of high-frequency foreign exchange data, we present evidence of time-of-day effects in foreign exchange returns through a significant tendency for currencies to depreciate during local trading hours. We confirm this pattern across a range of currencies and find that, in the case of EUR/USD, it can form a simple, profitable trading strategy. We also find that this pattern is present in order flow and suggest that both patterns relate to the tendency of market participants to be net purchasers of foreign exchange in their own trading hours. Data from alternative sources appear to corroborate that interpretation.
