This paper uses multi-period cross-sectional data on financial assets holdings to shed light on the postwar stability of money demand in the United States. I first present a new measure of the evolution of financial market participation, by relating participation to the extensive margins of money demand, and quantify the influence of wealth on participation decisions. I then relate the increase in participation to the period of "missing money" and to the subsequent higher interest rate elasticity of monetary aggregates. The paper indicates that time series estimations of money demand relationships are inherently flawed and tend to inappropriately suggest instability.
What are the drivers of the large Target2 (T2) balances that have emerged in the European Monetary Union since the start of the financial crisis in 2007? This paper examines the extent to which the evolution of national T2 balances can be statistically associated with cross-border financial flows and current account (CA) balances. In a quarterly panel spanning the years 1999 to 2012 and twelve countries, it is shown that while the CA and the evolution of T2 balances were unrelated until the start of the 2007 financial crisis, since then, the relation between these two variables has become statistically significant and economically sizeable. This reflects the partial "sudden stop" to private sector capital that funded CA imbalances beforehand. I next examine how different types of financial flows have evolved over the last years and how this can be related to the evolution of T2 balances. While changes in cross-border positions in the interbank market are associated with increasing T2 imbalances, cross-border inter-office flows between banks belonging to the same financial institution have reduced T2 imbalances. Flows to the banking sector that originate from private investors and non-financial firms are large in magnitude, but are only weakly correlated with the evolution of T2 balances; changes in banks' holdings of foreign government debt and deposit flows are strongly correlated with the post-2007 evolution of T2 balances. Overall, these findings point to a sizeable transfer of risk from the private to the public sector within T2 creditor nations the via the use of central bank liquidity.
In this paper, we examine the extent to which market structure and the way in which it affects pricing decisions of profit-maximizing firms can explain incomplete exchange rate passthrough. To this purpose, we evaluate how pass-through rates vary across trade partners and sectors depending on the mass and size distribution of firms affected by a particular exchange rate shock. In the first step of our analysis, we decompose bilateral exchange rate movements into broad US Dollar (USD) movements and trade-partner currency (TPC) movements. Using micro data on US import prices, we show that the pass-through rate following USD movements is up to four times as large as the pass-through rate following TPC movements and that the rate of pass-through following TPC movements is increasing in the trade partner's sector-specific market share. In the second step, we draw on the parsimonious model of oligopoly pricing featuring variable markups of Dornbusch (1987) and Atkeson and Burstein (2008) to show how the distribution of firms' market shares and origins within a sector affects the trade-partner specific pass-through rate. Third, we calibrate this model using our exchange rate decomposition and information on the origin of firms and their market shares. We find that the calibrated model can explain a substantial part of the variation in import price changes and pass-through rates across sectors, trade partners, and sector-trade partner pairs.
Exporting firms do not only decide how much of their products they ship abroad but also at which frequency. Doing so, they face a trade-off between saving on fixed costs per shipments (by shipping large amounts infrequently) and saving on storage costs (by delivering just in time with small and frequent shipments). The firm's optimal choice defines a mapping from size and frequency of shipments to fixed costs per shipment. We use a unique dataset of Swiss cross-border trade on the transaction level to analyze the size and shape of the underlying fixed costs. The data suggest that for the average Swiss exporter the fixed costs per shipment are economically important: about one percent of the value of export or at a net present value of 7790 CHF. We document that the imputed fixed costs per shipment correlate negatively with language commonalities, trade agreements and geographic proximity.
As it has proved difficult to explain the recent US house price boom on the basis of fundamentals, many observers have emphasised the role of speculation. This kind of argument is, however, indirect, as speculation is treated as a deviation from a benchmark. Our paper identifies house price expectation shocks directly, using a VAR with sign restrictions. House price expectation shocks are the most important driver of the US house price boom. We also show that a model-based measure of changes in price expectations leads a survey-based measure. Our baseline specification leaves the question of whether expectation shifts are realistic or unrealistic unanswered. In alternative specifications, we provide evidence that expectation shifts during the boom were largely unrealistic.
The US financial crisis and the later eurozone crisis have substantially impacted capital flows into and out of financial centers like Switzerland. We focus on the pattern of capital flows involving the Swiss banking industry. We first rely on balance-of-payment statistics and show that net banking inflows rose during the acute phases of the crises, albeit with a contrasting pattern. In the wake of the collapse of Lehman Brothers, net inflows were driven by a substantial retrenchment into the domestic market by Swiss banks. By contrast, net inflows from mid-2011 to mid-2012 were driven by large flows into Switzerland by foreign banks. We then use more detailed data from Swiss banking statistics which allow us to differentiate the situation across different banks and currencies. We show that, during the US financial crisis, the bank flows cycle was driven strongly by exposures in US dollars, and to a large extent by Swiss-owned banks. During the eurozone crisis, by contrast, the flight to the Swiss franc and move away from the euro was also driven by banks that are located in Switzerland, yet are foreign-owned. In addition, while the demand for the Swiss franc was driven by both foreign and domestic customers from mid-2011 to early 2013, domestic demand took a prominent role thereafter.
In this paper, we propose a modification of the three-pass regression filter (3PRF) to make it applicable to large mixed frequency datasets with ragged edges in a forecasting context. The resulting method, labeled MF-3PRF, is very simple but compares well to alternative mixed frequency factor estimation procedures in terms of theoretical properties, finite samle performance in Monte Carlo experiments, and empirical applications to GDP growth nowcasting and forecasting for the USA and a variety of other countries.
According to economic theory, the intertemporal budget constraint of households implies that a permanent increase in wealth should have a positive effect on consumer spending. Given the comparatively strong increase in Swiss household wealth over the past few years, the question of the extent to which changes in wealth influence expenditures of households has become of special interest for Switzerland. In this paper, I show that while the link among consumption, wealth and income was quite strong from 1981 to 2000, it has been very unstable since 2001. This fact suggests that the gap among the three variables, i.e., the deviation from long-run equilibrium, that has opened over the last few years is less likely to close. The results apply to aggregate wealth effects as well as to separate financial and housing wealth effects. Furthermore, I document several fragility issues related to the use of the cointegration approach to estimating wealth effects. These issues highlight the importance of carefully checking the robustness of the results, instead of looking just at one cointegration estimation method and only one time period. They also highlight the need for a non-cointegration approach to estimating wealth effects.
This paper empirically evaluates the predictive performance of the International Monetary Fund's (IMF) exchange rate assessments with respect to future exchange rate movements. The assessments of real trade-weighted exchange rates were conducted from 2006 to 2011, and were based on three state-of-the-art exchange rate models with a medium-term focus which were developed by the IMF. The empirical analysis using 26 advanced and emerging market economy currencies reveals that the 'diagnosis' of undervalued or overvalued currencies based on these models has significant predictive power with respect to future exchange rate movements, with one model outperforming the other two. The models are better at predicting future exchange rate movements in advanced and open economies. Controlling for the exchange rate regime does not increase the predictive power of the assessments.Furthermore, the directional accuracy of the IMF assessments is found to be higher than market expectations.
Foreign economic activity is a major determinant of export development. This paper presents an indicator for now- and forecasting exports, which is based on survey data that captures foreign economic perspectives. We construct an indicator by weighting foreign PMIs of main trading partners with their respective export shares. For two very trade exposed countries (Germany and Switzerland) the paper shows that the indicator based on foreign PMIs is strongly correlated with exports (total as well as goods exports). In an out-of-sample forecast comparison we employ MIDAS models to forecast the two different definitions of exports. We document that our export indicator performs very well relative to univariate benchmarks and relative to other major leading indicators using hard and soft data.
