Low interest rate policy and the use of reserve requirements in emerging markets

This paper sheds light on the link between the interest rate policy in large advanced economies with international funding and reserve currencies (the United States and the euro area) and the use of reserve requirements in emerging markets. Using reserve requirement data for 28 emerging markets from 1998 to 2012, we provide evidence that emerging market central banks tend to raise reserve requirements when interest rates in international funding markets decline or financial inflows accelerate, most likely to preserve financial stability. In contrast, when global liquidity risk rises and funding from the large advanced economies dries up, emerging markets lower reserve requirements.     

Capital flows and the boom–bust cycle: The case of Estonia

During 2000–2007, Estonia was among the fastest growing emerging market economies, but in late-2008 entered a deep recession. This paper examines shocks, institutions, and policies that have made Estonia's boom–bust cycle so severe. It finds that an open capital account, the prospect for EU entry, and the currency board facilitated massive capital inflows, which led to credit and real estate booms. In late-2008 a domestic slowdown was greatly amplified by the global financial and economic crisis. To resume sustainable growth, the country will need to regain competitiveness and rebalance resources to exports. Estonia's experience underscores the importance for other emerging market economies to retain some flexibility in their macroeconomic frameworks and approach capital account liberalization cautiously.     

Asymmetries between Rich and Poor Countries in Financial Crisis Responses: The Need for a Flow-of-Funds Approach

This paper focuses on the manner in which interest rates have been raised to, and sustained at, extremely high levels in developing and emerging market economies as a consequence of recent financial crises. By contrast rich market economies have typically lowered interest rates and injected liquidity in response to incipient financial crises. The paper first sketches the logic that lies behind extremely high interest rates (nominal and real) as an element of crisis resolution. It suggests that this reflects a money-phobic view of financial markets and also conflicts with some well-established economics. It then reviews the conventional wisdom about why richer economies have enjoyed sustained price stability in recent years and why this in turn has allowed their monetary authorities to be relaxed about injecting additional liquidity in response to LTCM (1998) and September 11 (2001)-type crises. It is pointed out that this conventional wisdom is also money-phobic in that it neglects the build up of corporate and government debt in bond and financial derivative form that has been associated with recent financial developments. This analysis helps to contest the common view that emerging market economies pay a higher price merely because their polices are "bad'. Finally, the paper reviews the manner in which the financial systems of developing and emerging market economies respond to the destabilization created by corrosively high real rates of interest. Even when bankruptcy arrangements are well established, certain new forms of financial flows and instruments are implicit in this response, but are invariably ignored in formal modelling.     

短期国际资本流动新趋势、对我国的影响及其防范

当前,全球资本流动总量小幅但不均衡回升,未来有可能缓慢增长;发展中国家资本市场的发展正在逐渐改变国际资本流动的结构;国际金融市场参与者的角色发生很大的变化;国际资本向新兴经济体特别是亚洲新兴经济体大量流动.在短期国际资本的持续冲击下,新兴经济体已有形成资产泡沫的风险,并且在未来仍有继续扩大的趋势.对于中国而言,热钱在中国的投机空间有限,短期内大规模持续流入的条件还不具备,温和流入并时有反复可能将成长期趋势.要摆脱国际热钱大规模流动带来的包括人民币升值压力在内的一系列困扰,必须采取疏堵结合的方式:一方面,采取有效的防御性措施,监控各类热钱,加强流入管制;另一方面,应重视疏导的作用,抑制泡沫膨胀,吸引中长期国际资本,防范和限制短期资本泛滥.     

Predicting interest rates using shrinkage methods,real-time diffusion indexes,and model combinations

In the context of predicting the term structure of interest rates, we explore the marginal predictive content of real-time macroeconomic diffusion indexes extracted from a “data rich” real-time data set, when used in dynamic Nelson–Siegel (NS) models of the variety discussed in Svensson (NBER technical report, 1994; NSS) and Diebold and Li (Journal of Econometrics, 2006, 130, 337–364; DNS). Our diffusion indexes are constructed using principal component analysis with both targeted and untargeted predictors, with targeting done using the lasso and elastic net. Our findings can be summarized as follows. First, the marginal predictive content of real-time diffusion indexes is significant for the preponderance of the individual models that we examine. The exception to this finding is the post “Great Recession” period. Second, forecast combinations that include only yield variables result in our most accurate predictions, for most sample periods and maturities. In this case, diffusion indexes do not have marginal predictive content for yields and do not seem to reflect unspanned risks. This points to the continuing usefulness of DNS and NSS models that are purely yield driven. Finally, we find that the use of fully revised macroeconomic data may have an important confounding effect upon results obtained when forecasting yields, as prior research has indicated that diffusion indexes are often useful for predicting yields when constructed using fully revised data, regardless of whether forecast combination is used, or not. Nevertheless, our findings also underscore the potential importance of using machine learning, data reduction, and shrinkage methods in contexts such as term structure modeling.     

Ethnic Fractionalization,Governance and Loan Defaults in Africa

We present a theoretical model of an imperfectly competitive loans market that is suitable for emerging economies in Africa. The model allows for variation in both the level of contract enforcement (the quality of governance) and the degree of market segmentation (the level of ethnic fractionalization). The model predicts a specific form of nonlinearity in the effects of these variables on loan default. Empirical analysis using African panel data for 110 individual banks in 28 countries over 2000–08 provides strong evidence for these predictions. Our results have important implications for the conditions under which policy reform will enhance financial development.     

Regional or global shock? A global VAR analysis of Asian economic and financial integration

This study employs a global vector autoregressive (GVAR) model to empirically investigate the viability of regional monetary arrangements in Asia. In marked contrast to the previous studies, we analyzed whether recent regional economic and financial integration in Asia were driven by global (U.S.) shock or regional (Japanese and Chinese) shock, using the GVAR model that allows global inter-linkages between domestic and foreign variables. By estimating generalized impulse responses of Asian economies’ real outputs and interest rates to global and regional shocks, we found that the Chinese shock exerted more real and financial influences on Asian economies than the U.S. shock. Another regional shock, i.e., the Japanese shock, had a far smaller influence on Asian economies. The relative importance of regional shocks originating from China needs to be considered when establishing regional monetary arrangements in Asia.     

Bilateral M&A activity from the Global South

This paper studies the factors associated with outbound bilateral mergers and acquisitions (M&A) activity by firms located in emerging economies. We document recent trends in emerging market M&A flows, which have risen dramatically over the past decade, and explore the factors that may have contributed to this rise. We find distinct patterns for M&A deals according to whether the acquisition targets are in other emerging economies or advanced countries, and that these differences can be attributed to differing theoretical motivations behind foreign direct investment. We also consider the implications of our model for future M&A originating in the Global South, in light of the global financial crisis of 2008.     

Trilemma policy convergence patterns and output volatility

We examine the development of open macroeconomic policy choices among developing economies from the perspective of the powerful “trilemma” hypothesis. We construct an index of divergence of the three trilemma policy choices, and evaluate its patterns in recent decades. We find that the three dimensions of the trilemma configurations are converging toward a “middle ground” among emerging market economies, equipped with managed exchange rate flexibility, underpinned by sizable holdings of international reserves, and intermediate levels of monetary independence and financial integration. We also find emerging market economies with more converged policy choices tend to experience smaller output volatility in the last two decades. Emerging markets with relatively low international reserves/GDP could experience higher levels of output volatility when they choose a policy combination with a greater degree of policy divergence while this heightened output volatility effect does not apply to economies with relatively high international reserves/GDP holding.     

Networks vs. market methods in high-tech venture fundraising: the impact of institutional environment

This study examines how institutional environmental factors, including cultural norm, state regulatory system and venture capital market, influence the high-tech entrepreneur's choice for using network vs. market methods when approaching prospective investors at the early stage of their new venture creation. We collected comparative data through on-site interviews and questionnaire survey with 128 high-tech entrepreneurs in Singapore (a newly industrialised economy) and 250 in Beijing, China (an emerging economy). Our findings suggest that a culture emphasising the value of social obligation, the under-development of the legal/regulatory system and the immaturity of the venture capital market increased the proclivity of entrepreneurs to use network methods. Moreover, entrepreneurs who value networks higher in social obligation than in information transfer are more likely to choose personal ties instead of business ties. This study enhances our understanding of how high-tech entrepreneurs in emerging economies choose between networks and market methods in venture fundraising, and offers suggestions on how public policy makers in these economies can improve the institutional environment of their regions to promote high-tech new venture creation.     

Credit default swaps and sovereign debt markets

This study investigates the link between the price discovery dynamics in sovereign credit default swaps (CDS) and bond markets and the degree of financial integration of emerging markets. Using CDS and sovereign bond spreads, the price discovery mechanism was tested using a vector error correction model. Financial integration is measured using news-based methods. We find that sovereign CDS and bond markets are co-integrated. In five out of seven sovereigns (71%), the bond market leads in price discovery by adjusting to new information regarding credit risk before CDS. In 29% of times, CDS markets are the source of price discovery. We also find a positive correlation of 0.67 between the degree of financial integration and the bond market information share. The evidence suggests that changes in sovereign credit risk and bond yields are significantly influenced by common external (global) factors, while country-specific factors play an insignificant role.     

Gross capital inflows and outflows: Twins or distant cousins?

We investigate the long-run relations and equilibrium correction mechanisms between gross capital inflows, outflows and global financial conditions for advanced (AE) and emerging market economies (EME). According to our results, the puzzling findings of the recent literature suggesting that domestic and foreign investors act as distant cousins, leading to capital inflows and outflows to act as twins, tend to be supported for the long run. The short-run relations, however, often appear to be consistent with the conventional theory suggesting that the behaviors of residents and non-residents do not systematically diverge from each other. Consistent with flight to safety concerns, capital outflows from EME and capital inflows to AE tend to increase in the long run in response to worsening global financial conditions. We find that these results essentially hold for the main components of capital flows as well.     

Credit-based early warning indicators of banking crises in emerging markets

This article explores the role of credit-based variables as early warning indicators (EWIs) of banking crises in the context of emerging economies. We collect data on bank and total credit to the private sector in emerging markets and evaluate the signalling performance by using the area under the receiver operating characteristics (ROC) curve (AUC). Our results show that nominal credit growth and the change in the credit-to-GDP ratio have the best signalling properties and significantly outperform the credit-to-GDP gap in almost all specifications for policy-relevant horizons. These findings are in stark contrast with the results on advanced economies, where the credit-to-GDP gap is the single best performing EWI. Our results emphasize the importance of caution when applying statistical methods calibrated for advanced markets to emerging economies.     

The macro-financial factors behind the crisis: Global liquidity glut or global savings glut?

It has been argued that the global financial crisis 2007–2009 was intrinsically related to two largely unprecedented phenomena in the global economy: (i) exceptionally benign financial market conditions as mirrored in historically low risk premia and buoyant asset price developments as well as (ii) an unprecedented widening of external imbalances. This paper explores to what extent these global trends can be understood as a reaction to three structural shocks to the macro-financial environment of the global economy: (i) monetary shocks (“excess liquidity” hypothesis), (ii) preference shocks (“savings glut” hypothesis), and (iii) investment shocks (“investment drought” hypothesis). In order to uniquely identify these shocks in an integrated framework, we estimate structural VARs for the two main regions with widening imbalances, the United States and emerging Asia, using sign restrictions that are compatible with standard New Keynesian and Real Business Cycle models. Our results show that (US) monetary policy shocks explain the largest part of the variation in imbalances and financial market prices. We find that savings shocks and investment shocks explain less of the variation. Hence, a “liquidity glut” may have been a more important driver of real and financial imbalances in the US and emerging Asia that ultimately triggered the global financial crisis.     

Economic policy uncertainty effects for forecasting future real economic activity

Recently introduced measures for economic policy uncertainty (EPU), included in the data from 1997 to 2016, have a role in forecasting out-of-sample values for future real economic activity for both the euro area and UK economies. The inclusion of EPU measures, either for the US, the UK or for overall European economies, improves the forecasting ability of models based on standard financial market information, especially for the period before the 2008 global crisis. However, during and after the crisis period, the slope of the yield curve and excess stock market returns improves the out-of-sample forecast performance the most compared to an AR-benchmark model. Hence, the EPU information is important in times of normal business cycles, but might contain similar information components to financial market return variables during turbulent crisis periods in the financial markets and in the real economy.     

Money market pressure in emerging economies: International contagion versus domestic determinants

Recent market turmoil has again raised the threat of banking crises worldwide. Might these crises be contagious internationally, or are fundamentals more likely to be responsible? This study creates monthly indices of “money market pressure” (MMP) for 20 emerging markets from 2002 to 2010, before using Vector Autoregressive (VAR) methods to test for various spillovers among money and foreign exchange markets. We find that MMP Granger-causes exchange market pressure (EMP) in most countries, but that causality does not run the other direction. Secondly, MMP seems to be more contagious in Southeast Asia than in Latin America or among large emerging markets globally, and the most financially open economies are most susceptible to “direct” spillovers that do not operate through exchange markets. Finally, when examining domestic influences in large emerging markets, output drops are most likely to increase MMP.     

Mining big data using parsimonious factor,machine learning,variable selection and shrinkage methods

A number of recent studies in the economics literature have focused on the usefulness of factor models in the context of prediction using “big data” (see Bai and Ng, 2008; Dufour and Stevanovic, 2010; Forni, Hallin, Lippi, & Reichlin, 2000; Forni et al., 2005; Kim and Swanson, 2014a; Stock and Watson, 2002b, 2006, 2012, and the references cited therein). We add to this literature by analyzing whether “big data” are useful for modelling low frequency macroeconomic variables, such as unemployment, inflation and GDP. In particular, we analyze the predictive benefits associated with the use of principal component analysis (PCA), independent component analysis (ICA), and sparse principal component analysis (SPCA). We also evaluate machine learning, variable selection and shrinkage methods, including bagging, boosting, ridge regression, least angle regression, the elastic net, and the non-negative garotte. Our approach is to carry out a forecasting “horse-race” using prediction models that are constructed based on a variety of model specification approaches, factor estimation methods, and data windowing methods, in the context of predicting 11 macroeconomic variables that are relevant to monetary policy assessment. In many instances, we find that various of our benchmark models, including autoregressive (AR) models, AR models with exogenous variables, and (Bayesian) model averaging, do not dominate specifications based on factor-type dimension reduction combined with various machine learning, variable selection, and shrinkage methods (called “combination” models). We find that forecast combination methods are mean square forecast error (MSFE) “best” for only three variables out of 11 for a forecast horizon of $h=1$, and for four variables when $h=3$ or $12$. In addition, non-PCA type factor estimation methods yield MSFE-best predictions for nine variables out of 11 for $h=1$, although PCA dominates at longer horizons. Interestingly, we also find evidence of the usefulness of combination models for approximately half of our variables when $h>1$. Most importantly, we present strong new evidence of the usefulness of factor-based dimension reduction when utilizing “big data” for macroeconometric forecasting.     

Supply chain and logistics innovations with the Belt and Road Initiative

The Belt and Road Initiative (BRI) is a massive, ambitious, long-term project initiated by the Chinese government, with participation from many other countries, to facilitate trade and improve logistics in an effort to promote global economic development. In this paper, we identified the supply chain and logistics innovations linked to the BRI. These innovations include new routes and modes for global trade, new supply chain design, reduction of cross-border logistics frictions, and entrepreneurial development. Examples of some of these innovations are emerging, while new ones are being developed. These innovations can enable businesses to improve their operational performances and create economic value. At the same time, to realize the full potentials of BRI, new work processes and technologies, incentive alignment, collaborations among businesses, and optimized planning are needed. This provides great opportunities for researchers to explore how to overcome barriers and achieve the full values of BRI.     

CORPORATE CAPITAL STRUCTURE AND HOW SOFT BUDGET CONSTRAINTS MAY AFFECT IT

Abstract.  This survey paper examines existing theories of capital structure and related empirical tests with the aim to derive theoretical as well empirically testable predictions about the implications of the soft budget constraint for corporate capital structure. We show that the soft budget constraint syndrome is relevant for a variety of institutional environments, from central planning to capitalist economic systems, and consider features of company financing patterns in various institutional contexts. Special attention is paid to emerging and transition economies where, with the development of financial markets, companies reduce their financial dependence on the state and begin to borrow from a variety of sources. However, due to the persistence of soft budget constraints, corporate capital structure in transition and emerging economies may still deviate significantly from the capital structure of companies operating under hard budget constraints.     

Board gender diversity and transparency of environmental,social and governance disclosure: Evidence from Malaysia

This study aims to investigate the effect of board gender diversity on the transparency of environmental, social, and governance (ESG) disclosures in an emerging market such as Malaysia. Dataset is comprised of 568 firm-year observations from 78 firms listed on the Bursa Malaysia. Ordinary least squares regression analysis of the data shows that ESG disclosure scores are significantly improved with the increasing presence of women directors on corporate boards. However, when the individual components are studied, the impact of board gender diversity varies. This study contributes to the limited but growing literature on ESG reporting quality and board gender diversity especially in emerging economies.