Increasing the credibility of the twin birth instrument

Twin births are an important instrument for the endogenous fertility decision. However, twin births are not exogenous either as dizygotic twinning is correlated with maternal characteristics. Following the medical literature, we assume that monozygotic twins are exogenous, and construct a new instrument, which corrects for the selection although monozygotic twinning is usually unobserved in survey and administrative datasets. Using administrative data from Sweden, we show that the usual twin instrument is related to observed and unobserved determinants of economic outcomes, while our new instrument is not. In our applications we find that the classical twin instrument underestimates the negative effect of fertility on labor income. This finding is in line with the observation that high earners are more likely to delay childbearing and hence have a higher risk to get dizygotic twins.     

Do Rising Top Incomes Spur Economic Growth? Evidence From OECD Countries Based on a Novel Identification Strategy

We investigate the causal relationship between the growth rate of top income shares and economic growth in 12 OECD economies for the period 1950–2010. To analyze patterns of short- and long-run causality, we build upon recent advances in structural-vector autoregressive modeling of non-Gaussian systems. This framework allows us to discriminate between rival transmission channels by means of dependence tests, since independent shocks are unique for a particular causation pattern. We consider the share of income accruing to the top 1 percent (1), to the next 9 percent (9), and to the top decile (10). While structural models display considerable heterogeneity across countries, mean group and pooled results strongly favor a specific transmission pattern. In particular, 1 has a long-run positive impact on economic development. This result, which is also confirmed by identified impulse-response functions, is particularly evident for the post-1980 period.     

Risk forecasting in (T)GARCH models with uncorrelated dependent innovations

(G)ARCH-type models are frequently used for the dynamic modelling and forecasting of risk attached to speculative asset returns. While the symmetric and conditionally Gaussian GARCH model has been generalized in a manifold of directions, model innovations are mostly presumed to stem from an underlying IID distribution. For a cross section of 18 stock market indices, we notice that (threshold) (T)GARCH-implied model innovations are likely at odds with the commonly held IID assumption. Two complementary strategies are pursued to evaluate the conditional distributions of consecutive TGARCH innovations, a non-parametric approach and a class of standardized copula distributions. Modelling higher order dependence patterns is found to improve standard TGARCH-implied conditional value-at-risk and expected shortfall out-of-sample forecasts that rely on the notion of IID innovations.     

Structural vector autoregressions with Markov switching: Combining conventional with statistical identification of shocks

In structural vector autoregressive (SVAR) analysis a Markov regime switching (MS) property can be exploited to identify shocks if the reduced form error covariance matrix varies across regimes. Unfortunately, these shocks may not have a meaningful structural economic interpretation. It is discussed how statistical and conventional identifying information can be combined. The discussion is based on a VAR model for the US containing oil prices, output, consumer prices and a short-term interest rate. The system has been used for studying the causes of the early millennium economic slowdown based on traditional identification with zero and long-run restrictions and using sign restrictions. We find that previously drawn conclusions are questionable in our framework.     

Modelling Hospital Admission and Length of Stay by Means of Generalised Count Data Models

For a large heterogeneous group of patients, we analyse probabilities of hospital admission and distributional properties of lengths of hospital stay conditional on individual determinants. Bayesian structured additive regression models for zero‐inflated and overdispersed count data are employed. In addition, the framework is extended towards hurdle specifications, providing an alternative approach to cover particularly large frequencies of zero quotes in count data. As a specific merit, the model class considered embeds linear and nonlinear effects of covariates on all distribution parameters. Linear effects indicate that the quantity and severity of prior illness are positively correlated with the risk of hospital admission, while medical prevention (in the form of general practice visits) and rehabilitation reduce the expected length of future hospital stays. Flexible nonlinear response patterns are diagnosed for age and an indicator of a patients' socioeconomic status. We find that social deprivation exhibits a positive impact on the risk of admission and a negative effect on the expected length of future hospital stays of admitted patients. Copyright © 2015 John Wiley & Sons, Ltd.     

STRUCTURAL VECTOR AUTOREGRESSIONS: CHECKING IDENTIFYING LONG‐RUN RESTRICTIONS VIA HETEROSKEDASTICITY

Long‐run restrictions have been used extensively for identifying structural shocks in vector autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be checked by utilizing changes in volatility. This paper reviews and contrasts the volatility models that have been used for this purpose. Three main approaches have been used, exogenously generated changes in the unconditional residual covariance matrix, changing volatility modelled by a Markov switching mechanism and multivariate generalized autoregressive conditional heteroskedasticity models. Using changes in volatility for checking long‐run identifying restrictions in structural VAR analysis is illustrated by reconsidering models for identifying fundamental components of stock prices.     

Internationalisation of technology-oriented firms in Germany and the UK

Based on longitudinal data, this article examines empirically the long-term export behaviour of German and British technology-oriented firms founded between 1987 and 1996. Applying logit models, the results show that firms can overcome high entry costs by acquiring firm-specific assets. Similarly, firm-specific resources prevent high-tech companies from exiting the international market. The strategic role of investment in R&D is stressed in particular by the data.

Financial opening in developing countries

Many developing countries are currently considering liberalisation of external capital flows. While the ultimate objective of financial opening is to raise efficiency and growth, the reform process must be carefully designed to achieve these results. A recent conference has discussed the policy choices.     

Product-design perception and brand strength

In this article, we present an approach to understanding product design from a cognitive psychologist’s view. We show what cognitive processes are involved in perceiving products. Moreover, we discuss how these processes are related to the mental formation of brands and how they affect perceivers’ appreciation of a product’s design.