This paper discusses the problems associated with using information about the signs of certain magnitudes as a basis for drawing structural conclusions in vector autoregressions. We also review available tools to solve these problems. For illustration we use Dahlhaus and Vasishtha’s (2019) study of the effects of a U.S. monetary contraction on capital flows to emerging markets. We explain why sign restrictions alone are not enough to allow us to answer the question and suggest alternative approaches that could be used.

This paper investigates the role of the fiscal and economic record of the incumbent government in shaping the price response of sovereign bonds and stocks to the election outcome in emerging markets and developed countries. For sovereign bonds in emerging markets, we find robust evidence for higher cumulative abnormal returns (CARs) if a government associated with a relatively low primary fiscal balance is voted out of office compared to elections where the fiscal balance was relatively high. This effect of the incumbent government's fiscal record is significantly more pronounced in the presence of high sovereign default risk and strong political veto players, whereas the quality of institutions does not explain differences in effects for different events. We do not find robust effects of the government's fiscal record for developed countries and stocks.

We show that emergency liquidity provision by the Federal Reserve transmitted to non-U.S. banking markets. Based on manually collected holding company structures, we identify banks in Germany with access to U.S. facilities. Using detailed interest rate data reported to the German central bank, we compare lending and borrowing rates of banks with and without such access. U.S. liquidity shocks cause a significant decrease in the short-term funding costs of the average German bank with access. This reduction is mitigated for banks with more vulnerable balance sheets prior to the inception of emergency liquidity. We also find a significant pass-through in terms of lower corporate credit rates charged for banks with the lowest pre-crisis leverage, US-dollar funding needs, and liquidity buffers. Spillover effects from U.S. emergency liquidity provision are generally confined to short-term rates.

This paper discusses the problems associated with using information about the signs of certain magnitudes as a basis for drawing structural conclusions in vector autoregressions. We also review available tools to solve these problems. For illustration we use Dahlhaus and Vasishtha's (2019) study of the effects of a U.S. monetary contraction on capital flows to emerging markets. We explain why sign restrictions alone are not enough to allow us to answer the question and suggest alternative approaches that could be used.

Using daily data for 34 emerging markets in the period 1994-2016, we find robust evidence that higher export commodity prices are associated with higher sovereign bond returns (indicating lower sovereign risk). The economic effect is especially pronounced for heavy commodity exporters. Examining the drivers, we find, first, that commodity-dependence is higher for countries that export large volumes of volatile commodities and that the effect increases in times of recessions, high inflation, and expansionary U.S. monetary policy. Second, the importance of raw material prices for sovereign financing can likely be mitigated if a country improves institutions and tax systems, attracts FDI inflows, invests in manufacturing, machinery and infrastructure, builds up reserve assets and opens capital and trade accounts. Third, the concentration of commodities within a country’s portfolio, its government indebtedness or amount of received development assistance appear to be only of secondary importance for commodity-dependence.

One explanation for the emergence of the housing market bubble and the subprime crisis is that increases in individuals’ income led to higher increases in the amount of mortgage loans demanded, especially for the middle class. This hypothesis translates to an increase in the income elasticity of mortgage loan demand before 2007. Using applicant‐level data, we test this hypothesis and find that the income elasticity of mortgage loan demand in fact declines in the years before 2007, especially for the mid‐ and lower‐middle income groups. Our finding implies that increases in house prices were not matched by increases in loan applicants’ income.

We introduce a novel currency risk measure based on American Depositary Receipts (ADRs). Using an augmented ADR pricing model, we exploit investors’ exposure to potential devaluation losses to derive an indicator of currency risk. Using weekly data for a sample of 807 ADRs located in 21 emerging markets over the 1994–2014 period, we find that a deterioration in the fiscal balance and higher inflation increase currency risk. Interaction models reveal that the fiscal balance and inflation drive the determination of currency risk for countries with poor sovereign rating, low foreign reserves, low capital account openness and managed float regimes.

• Signs of a slowing world economy are piling up: Since the beginning of the year purchasing manager indices have been declining globally, in summer higher US interest rates led investors to withdraw capital from emerging markets, and as a consequence, capital costs rose and currencies depreciated in many emerging markets economies. In October stock prices decreased markedly worldwide including the US, despite the strong upswing in this country. • As a consequence of the turmoil on financial markets, monetary conditions in many emerging economies are no longer favorable. What ultimately counts for the prospects of the global economy, is, however, the performance of the US, the Euro area, China and Japan. The upswing in the US appears stable enough to continue well into 2019. While at present the rest of the group appears to lose momentum, there is a good chance that production in each of these economies will still expand at rates that are close to their potential growth. Further protectionist rounds are the most important risk to this scenario. • In the first half of the current year the euro area economy expanded at a markedly slower rate than in 2017, about 0.4% per quarter, but still substantial. Rising risk premia on Italian assets will probably force banks in this large country to tighten credit conditions, and a slowing world trade will dent export growth. All in all, we expect GDP growth in the euro area to go down from 2.4% in 2017 to 2.0% in 2018 and to 1.7% in 2019. • Employment continues to expand and vacancy rates are at present higher than in 2017. As a consequence, wages rise more quickly: nominal compensations per employee started accelerating early in 2017, and negotiated wages followed at the beginning of 2018. Wage inflation of slightly below 2.5% and healthy growth in employment raise real labor incomes markedly. • Our forecasts are based on the assumption that rating agencies will continue as-signing investment grade to the Italian government debt, and that the Italian government and the European Commission will find a compromise about the draft budget of the country in the coming weeks. Another assumption is that the UK will not exit the EU in an unorderly way in March 2019.

In complex systems, statistical dependencies between individual components are often considered one of the key mechanisms which drive the system dynamics observed on a macroscopic level. In this paper, we study cross-sectional time-lagged dependencies in financial markets, quantified by nonparametric measures from information theory, and estimate directed temporal dependency networks in financial markets. We examine the emergence of strongly connected feedback components in the estimated networks, and hypothesize that the existence of information feedback in financial networks induces strong spatiotemporal spillover effects and thus indicates systemic risk. We obtain empirical results by applying our methodology on stock market and real estate data, and demonstrate that the estimated networks exhibit strongly connected components around periods of high volatility in the markets. To further study this phenomenon, we construct a systemic risk indicator based on the proposed approach, and show that it can be used to predict future market distress. Results from both the stock market and real estate data suggest that our approach can be useful in obtaining early-warning signals for crashes in financial markets.

The role of the financial system to absorb and to intermediate commodity boom induced windfall gains efficiently presents one of the most pressing issues for developing economies. Using an exogenous increase in iron ore prices in March 2005, I analyse the role of regional bank branch networks in Brazil in reallocating capital from affected to non-affected regions. For the period from March 2004 to March 2006, I find that branches directly exposed to this shock by their geographical location experience an increase in deposit growth in the post-shock period relative to non-affected branches. Given that these deposits are not reinvested locally, I further show that branches located in the non-affected region increase lending growth depending on their indirect exposure to the booming regions via their branch network. Even tough, these results provide evidence against a Dutch Disease type crowding out of the non-iron ore sector, further evidence suggests that this capital reallocation is far from being optimal.