Exchange rate pass-through in the global economy – the role of emerging market economies

This paper estimates export and import price equations for 41 countries –including 28 emerging market economies. Further, it relates the estimated elasticities to structural factors and tests for statistical breaks in the relation between trade prices and exchange rates. Results indicate that (i) the elasticity of trade prices in emerging markets is sizeable, but not significantly higher than in advanced economies; (ii) such elasticity is primarily influenced by macroeconomic factors such as the exchange rate regime and the inflationary environment, although microeconomic factors such as product differentiation also play a role; (iii) export and import price elasticities tend to be strongly correlated across countries; (iv) pass-through to import prices has declined in some advanced economies, noticeably the United States; this is consistent with a rise in pricing-to-market in several EMEs and especially with a change in the geographical composition of U.S. imports.emerging market economies; exchange rate pass-through; pricing-to-market; local and producer currency pricing; exchange rate regime

Macro-financial vulnerabilities and future financial stress - Assessing systemic risks and predicting systemic events

This paper develops a framework for assessing systemic risks and for predicting (out-of-sample) systemic events, i.e. periods of extreme financial instability with potential real costs. We test the ability of a wide range of “stand alone” and composite indicators in predicting systemic events and evaluate them by taking into account policy makers’ preferences between false alarms and missing signals. Our results highlight the importance of considering jointly various indicators in a multivariate framework. We find that taking into account jointly domestic and global macro-financial vulnerabilities greatly improves the performance of discrete choice models in forecasting systemic events. Our framework shows a good out-of-sample performance in predicting the last financial crisis. Finally, our model would have issued an early warning signal for the United States in 2006Q2, 5 quarters before the emergence of money markets tensions in August 2007.early warning indicators; asset price booms and busts; financial stress; macro-prudential policies

Housing and equity wealth effects of Italian households

The study quantifies stock market and housing market wealth effects on households' non-durable consumption using Italian household panel data (SHIW) of 1989-2002. We found all households react similarly to aggregate housing and stock market gains. We also found statistically and economically significant housing wealth effects with a marginal propensity to consume out of idiosyncratic housing wealth gains to be over 8 percent. The results from idiosyncratic equity wealth e¤ects were lower, at around 0.4 percent. We also found that older households react more to changes in housing wealth. JEL Classification: D12, E21Equities, housing, Marginal Propensity to Consume

Mapping the state of financial stability

The paper uses the Self-Organizing Map for mapping the state of financial stability and visualizing the sources of systemic risks as well as for predicting systemic financial crises. The Self-Organizing Financial Stability Map (SOFSM) enables a two-dimensional representation of a multidimensional financial stability space that allows disentangling the individual sources impacting on systemic risks. The SOFSM can be used to monitor macro-financial vulnerabilities by locating a country in the financial stability cycle: being it either in the pre-crisis, crisis, post-crisis or tranquil state. In addition, the SOFSM performs better than or equally well as a logit model in classifying in-sample data and predicting out-of-sample the global financial crisis that started in 2007. Model robustness is tested by varying the thresholds of the models, the policymaker’s preferences, and the forecasting horizons. JEL Classification: E44, E58, F01, F37, G01macroprudential supervision, prediction, Self-Organizing Map (SOM), Systemic financial crisis, systemic risk, visualization

Has emerging Asia decoupled? An analysis of production and trade linkages using the Asian international input-output table

Due to the emergence of global production networks, trade statistics have became less accurate in describing the dependence of emerging Asia on external demand. This paper analyses, using an update of the Asian International Input-Output (AIO) table, the interdependence of emerging Asian countries, the United States, the EU15, and Japan via trade and production linkages. According to the results, we do not find evidence of the decoupling of emerging Asia from the rest of the world. On the contrary, we find evidence on increasing trade integration, both globally and regionally. Nonetheless, our analysis indicates that emerging Asia’s dependence on exports is only about one-third of its GDP, i.e. well below the 50% exposure suggested by trade data. This finding can be explained by the high import content of exports in these economies, which is a result of the increasing segmentation of production across the region. JEL Classification: F14, C67, E23Asian International Input-Output table, decoupling, Emerging Asia, real linkages, resilience

Mapping the State of Financial Stability

The paper uses the Self-Organizing Map for mapping the state of financial stability and visualizing the sources of systemic risks on a two-dimensional plane as well as for predicting systemic financial crises. The Self-Organizing Financial Stability Map (SOFSM) enables a two-dimensional representation of a multidimensional financial stability space and thus allows disentangling the individual sources impacting on systemic risks. The SOFSM can be used to monitor macro-financial vulnerabilities by locating a country in the financial stability cycle: being it either in the pre-crisis, crisis, post-crisis or tranquil state. In addition, the SOFSM performs better than or equally well as a logit model in classifying in-sample data and predicting out-of-sample the global financial crisis that started in 2007. Model robustness is tested by varying the thresholds of the models, the policymaker’s preferences, and the forecasting horizon.systemic financial crisis; systemic risk; self-organizing maps; visualisation; prediction; macroprudential supervision