Balance of payments accounting and exchange rate dynamics

The balance of payments is an accounting identity. Many wonder how the current and capital accounts, which add up to zero, can influence exchange rates. This paper shows how payment flows arising from balance of payments imbalances affect the demands for different currencies in the foreign exchange market over time. Based on a dynamical system approach, the paper demonstrates how international payments evolve depending on the joint dynamic behaviour of different balance of payments components. It finds that international payments and exchange rates interact in fundamentally different ways depending on whether a country restricts its capital inflows and outflows, whether capital flows are accommodating or autonomous and whether the exchange rate is fixed, flexible or, say, governed by a crawling peg. Empirical evidence from major industrial countries as well as from countries hit by currency crises support the paper's theoretical predictions.     

Optimizing international portfolios with options and forwards

We develop a stochastic programming model to address in a unified manner a number of interrelated decisions in international portfolio management: optimal portfolio diversification and mitigation of market and currency risks. The goal is to control the portfolio’s total risk exposure and attain an effective balance between risk and expected return. By incorporating options and forward contracts in the portfolio optimization model we are able to numerically assess the performance of alternative tactics for mitigating exposure to the primary risks. We find that control of market risk with options has more significant impact on portfolio performance than currency hedging. We demonstrate through extensive empirical tests that incremental benefits, in terms of reducing risk and generating profits, are gained when both the market and currency risks are jointly controlled through appropriate means.     

Pricing options on scenario trees

We examine valuation procedures that can be applied to incorporate options in scenario-based portfolio optimization models. Stochastic programming models use discrete scenarios to represent the stochastic evolution of asset prices. At issue is the adoption of suitable procedures to price options on the basis of the postulated discrete distributions of asset prices so as to ensure internally consistent portfolio optimization models. We adapt and implement two methods to price European options in accordance with discrete distributions represented by scenario trees and assess their performance with numerical tests. We consider features of option prices that are observed in practice. We find that asymmetries and/or leptokurtic features in the distribution of the underlying materially affect option prices; we quantify the impact of higher moments (skewness and excess kurtosis) on option prices. We demonstrate through empirical tests using market prices of the S&P500 stock index and options on the index that the proposed procedures consistently approximate the observed prices of options under different market regimes, especially for deep out-of-the-money options.     

Lemmings in the bond market? An empirical analysis of the term structure of credit spreads

The paper examines the credit spread between government and corporate bonds at different maturities. Theoretical models assume that credit risk premiums for high quality firms monotonously increase with maturity. We find evidence suggesting that bonds issued at maturities attracting the highest issuance volumes tend to have credit risk premiums that are on average 10 to 15 basis points higher than issues at nonconventional maturities. These results point out a shortcoming of existing theoretical models and show that the credit yield curve is not smooth, but affected by the local supply of issues at various parts of the yield curve. In addition, the empirical evidence presented in this paper indicates that firms utilizing the bond markets for funding could lower their funding costs by shifting the term of their debt away from the most commonly targeted maturities.

Impact investments,evil investments,and something in between: Comparing social banks' investment criteria and strategies with depositors' investment preferences

Since the global financial crisis in 2007, social banks have been flooded with deposits. Previous studies have indicated that customers hold deposits with social banks due to social banks' special placement of assets. However, to date it has been far from clear how social banks select their investments, and consequently to what extent the placement of assets meets depositors' preferences. The purpose of this paper is, therefore, to investigate whether the characteristics of social banks’ placement of assets are relevant to depositors’ choice of social banks. A two-stage study is conducted, using data collected via a document analysis of social banks' investment criteria, a survey of social banks, and an online survey of 609 depositors. The results imply that the characteristics of social banks' placement of assets are indeed relevant to depositors' choice of social banks, but do not explain customer behaviour entirely. Furthermore, the findings indicate that a relevant proportion of customers hold deposits with social banks to avoid “evil” rather than necessarily creating “good.” Based on the findings, a theoretical framework of depositors' choice of social banks is presented that goes far beyond previous explanations by considering various types of social depositors, banks, and borrowers.     

An ‘Algorithmic Links with Probabilities’ Concordance for Trademarks with an Application Towards Bilateral IP Flows

Trademarks (TMs) shape the competitive landscape of markets for goods and services in all countries. As a key element of branding, they can inform consumers about the quality and content of goods and services. Yet, researchers are largely unable to conduct rigorous empirical analysis of TMs in the global economy because TM data and economic data are organised differently and cannot be analysed jointly at the industry or sector level. We propose an ‘algorithmic links with probabilities’ (ALP) approach to match TM data to economic data and enable joint analysis with these data. Specifically, we construct a NICE class‐level concordance that maps TM data into trade and industry categories forward and backward. This concordance allows researchers to analyse differences in TM usage across both economic and TM sectors. We apply this ALP concordance for TMs to characterise patterns in TM registrations across countries and industries and to investigate some key determinants of international technology flows by comparing bilateral TM registrations and bilateral patent grants. We find that international patenting and TM flows are jointly determined by trade‐related influences with significant differences in intellectual property usage across industry sectors and income levels.     

USING EL NIÑO-SOUTHERN OSCILLATION CLIMATE DATA TO IMPROVE FOOD POLICY PLANNING IN INDONESIA

Despite the impact of El Niño-Southern Oscillation (ENSO) events on climate in the Indo-Pacific region, models linking ENSO-based climate variability to Indonesian cereal production are not well developed. This study measures connections among sea-surface temperature anomalies (SSTAs), rainfall, and Indonesian rice and corn production from 1971 to 1998. Year-to-year August SSTA fluctuations explain about half the interannual variance in paddy production during the main (wet) season. These effects are cumulative for rice: during strong El Niño years, wet season production shortfalls are not made up subsequently. For corn, the cumulative area sown is actually higher in El Niño years than La Niña years. Indonesia's paddy production varies on average by 1.4 million tons for every 1°C change in August SSTAs. The paper illustrates how an SSTA model might assist policy makers with budgetary processes, and private sector cereal traders with framing production expectations.     

Measuring human development: a stochastic dominance approach

We consider a weighting scheme that yields a best-case scenario for measured human development such as the official equally-weighted Human Development Index (HDI) using an approach that relies on consistent tests for stochastic dominance efficiency. We compare the official equally-weighted HDI to all possible indices constructed from a set of individual components to obtain the most optimistic scenario for development. In the best-case scenario index education is weighted considerably more than the other two components, per capita income and life expectancy, relative to the weight that it gets in the official equally-weighted index. It also turns out that the improvement in the official HDI is mainly driven by improvements over time in the education index, the component moving fastest relative to its targets, when compared with per capita income and life expectancy. We find that the best-case scenario hybrid index leads to a marked improvement of measured development over time when compared with the official equally-weighted HDI.     

The effect of regulatory scrutiny: Asymmetric cost pass-through in power wholesale and its end

We find an asymmetric pass-through of European emission allowance (EUA) prices to wholesale electricity prices in Germany and show that this asymmetry disappeared in response to a report on investigations by the competition authority. The asymmetric pricing pattern, however, was not detected at the time of the report, nor had it been part of the investigations. Our results therefore provide evidence for the deterring effect of regulatory monitoring on firms which exhibit non-competitive pricing behavior. We do not find any asymmetric pass-through of EUA prices in recent years. Several robustness checks support our results.