Tuomas A. Peltonen

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 chapter analyses, using an update of the Asian International Input–Output (AIO) table, the interdependence of emerging Asian economies, 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 Asias dependence on exports is only about one-third of its GDP, that is, 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.

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.

Fundamentals, Financial Factors, and the Dynamics of Investment in Emerging Markets

The paper uses a panel vector autoregression approach to analyze the dynamics of the transition of investment to shocks to fundamental and financial factors in emerging market economies. By relying on a panel of thirty-one emerging economies and quarterly frequency data for the period 1990:1-2008:3, we show that (1) investment sluggishly adjusts to its own shocks; (2) gross domestic product and equity price shocks have a positive and sizable impact on investment; (3) unexpected variation in the cost of capital and the lending rate has a negative effect on investment; and (4) the response of investment to credit market developments seems to be driven by the demand side. In addition, the effects of equity price shocks appear to be similar for emerging Asia and Latin America, but credit shocks are more important in Latin America. Moreover, shocks to the lending rate have a pronounced and negative impact in emerging European markets. Finally, we show that the stock market bubbles may have encouraged real investment during the 1990s.

Booms and Busts in China’s Stock Market: Estimates Based on Fundamentals

This article empirically models Chinas stock prices using conventional fundamentals: corporate earnings, risk-free interest rate and a proxy for equity risk premium. It uses the estimated long-run stock price misalignments to date booms and busts, and analyses equity market reforms and excess liquidity as potential drivers of these stock price misalignments. Results show that Chinas equity prices can be well modelled using fundamentals, but that various booms and busts can be identified. Policy actions, either taking the form of deposit rate changes, equity market reforms or excess liquidity, have significantly contributed to these misalignments.

Systemic Risk Spillovers in the European Banking and Sovereign Network

We propose a framework for estimating network-driven time-varying systemic risk contributions that is applicable to a high-dimensional financial system. Tail risk dependencies and contributions are estimated based on a penalized two-stage fixed-effects quantile approach, which explicitly links bank interconnectedness to systemic risk contributions. The framework is applied to a system of 51 large European banks and 17 sovereigns through the period 2006 to 2013, utilizing both equity and CDS prices. We provide new evidence on how banking sector fragmentation and sovereign-bank linkages evolved over the European sovereign debt crisis and how it is reflected in network statistics and systemic risk measures. Illustrating the usefulness of the framework as a monitoring tool, we provide indication for the fragmentation of the European financial system having peaked and that recovery has started.

Modelling Inflation in China - A Regional Perspective

We model provincial inflation in China during the reform period. In particular, we are interested in the ability of the hybrid New Keynesian Phillips Curve (NKPC) to capture the inflation process at the provincial level. The study highlights differences in inflation formation and shows that the NKPC provides a reasonable description of the inflation process only for the coastal provinces. A probit analysis suggests that the forward-looking inflation component and the output gap are important inflation drivers in provinces that have advanced most in marketisation of the economy and have most likely experienced excess demand pressures. These results have implications for the relative effectiveness of monetary policy across the Chinese provinces.

Characterising the Financial Cycle: A Multivariate and Time-Varying Approach

We demonstrate that financial cycles (identified as common fluctuations in credit and asset prices, proxying balance-sheet leverage) strongly differ across countries, e.g., in duration. This is contradictory to a similar duration assumption inherent in prevalent proxies of financial cycles, such as the Basel III credit-to-GDP gap guiding countercyclical capital buffers. Against this backdrop, we propose a methodology for constructing financial cycles relaxing the similar-duration assumption and observe an improved capacity in predicting financial crises. Specifically, we use credit and asset prices as inputs to our methodology and show that constructed financial cycles significantly outperform the credit-to-GDP gap in predicting financial crises.

Interconnectedness of the Banking Sector as a Vulnerability to Crises

This paper uses domestic and cross-border linkages to measure the interconnectedness of the banking sector, and relates it to banking crises in Europe. Beyond cross-border financial linkages of the banking sector, we also account for financial linkages to the other main financial and non-financial sectors within the economy. We enrich conventional early-warning models using macro-financial vulnerabilities, by including measures of banking sector centrality as potential determinants of banking crises. Our results show that a more central position of the banking sector in these so-called macro-networks significantly increases the probability of a banking crisis. By analyzing the different types of risk exposures, our evidence shows that credit as well as market risks are important sources of vulnerabilities. Finally, the results show that early-warning models augmented with interconnectedness measures outperform traditional models in terms of out-of-sample predictions of recent banking crises in Europe.

Comparing Different Early Warning Systems: Results from a Horse Race Competition Among Members of the Macro-Prudential Research Network

Over the recent decades researchers in academia and central banks have developed early warning systems (EWS) designed to warn policy makers of potential future economic and financial crises. These EWS are based on diverse approaches and empirical models. In this paper we compare the performance of nine distinct models for predicting banking crises resulting from the work of the Macroprudential Research Network (MaRs) initiated by the European System of Central Banks. In order to ensure comparability, all models use the same database of crises created by MaRs and comparable sets of potential early warning indicators. We evaluate the models’ relative usefulness by comparing the ratios of false alarms and missed crises and discuss implications for pratical use and future research. We find that multivariate models, in their many appearances, have great potential added value over simple signalling models. One of the main policy recommendations coming from this exercise is that policy makers can benefit from taking a broad methodological approach when they develop models to set macro-prudential instruments.

How Does Risk Flow in the Credit Default Swap Market

We develop a framework to analyse the Credit Default Swaps (CDS) market as a network of risk transfers among counter-parties. From a theoretical perspective, we introduce the notion of flow-of-risk and provide sufficient conditions for a bow-tie network architecture to endogenously emerge as a result of intermediation. This architecture shows three distinct sets of counter-parties: i) Ultimate Risk Sellers (URS), ii) Dealers (indirectly connected to each other), iii) Ultimate Risk Buyers (URB). We show that the probability of widespread distress due to counter-party risk is higher in a bow-tie architecture than in more fragmented network structures. Empirically, we analyse a unique global dataset of bilateral CDS exposures on major sovereign and financial reference entities in 2011-2014. We find the presence of a bow-tie network architecture consistently across both reference entities and time, and that the flow-of-risk originates from a large number of URSs (e.g. hedge funds) and ends up in a few leading URBs, most of which are non-banks (in particular asset managers). Finally, the analysis of the CDS portfolio composition of the URBs shows a high level of concentration: in particular, the top URBs often show large exposures to potentially correlated reference entities.