Macroeconometric testing of the rational expectations and structural neutrality hypotheses for the United States

Empirical tests of the neutrality of money growth found in recent literature are tests of the joint hypothesis of rational expectations and structural neutrality. Although tests of this joint hypothesis are informative, it is also important to gain information on the accuracy of its constituents. This paper presents the application of a methodology capable of providing information on the empirical validity of the rational expectations, structural neutrality, and joint hypotheses. Tests of these hypotheses are performed on the basis of FIML estimation of an extended version of a model recently presented by Robert Barro, using U.S. data for 1946–1973.     

Does a clustered location matter for high-technology companies' performance? The case of biotechnology in the Netherlands

Young entrepreneurial companies in biotechnology tend to cluster in space, nearby research universities and research centers. This pattern is often ascribed to the availability of external economies, mainly local knowledge spillovers that help to reduce the uncertainty from a disruptive technology faced by these companies. Given a shortage of empirical research on cluster advantages and performance of clustered companies, we present results of a comparative analysis of clustered and non-clustered companies in biotechnology and Bionanotechnology in the Netherlands. It appears that, among other influences, a clustered location has no significant influence on innovation and speed of growth. However, a location in the largest cluster (Leiden) does contribute to a better performance in terms of innovativeness compared with all other locations. The kind of external economies involved seems to vary according to the stage in the knowledge value chain and the segment in biotechnology industry. Knowledge spillovers tend to be local for companies involved in new drugs and diagnostics research only in the first stage of the knowledge chain and for service companies regardless of the stage in the knowledge chain.     

Inside the bank lending channel

This paper tests cross-sectional differences in the effectiveness of the bank lending channel. The results, derived from a comprehensive sample of Italian banks, suggest that heterogeneity in the monetary policy pass-through exists. After a monetary tightening the decrease in lending is lower for well-capitalized banks that are perceived as less risky by the market and are better able to raise uninsured deposits. Liquid banks can protect their loan portfolio against monetary tightening simply by drawing down cash and securities. The presence of internal capital markets in bank holding companies also contributes to insulate monetary shocks. Bank size is never relevant.     

Tempered stable and tempered infinitely divisible GARCH models

In this paper, we introduce a new GARCH model with an infinitely divisible distributed innovation. This model, which we refer to as the rapidly decreasing tempered stable (RDTS) GARCH model, takes into account empirical facts that have been observed for stock and index returns, such as volatility clustering, non-zero skewness, and excess kurtosis for the residual distribution. We review the classical tempered stable (CTS) GARCH model, which has similar statistical properties. By considering a proper density transformation between infinitely divisible random variables, we can find the risk-neutral price process, thereby allowing application to option-pricing. We propose algorithms to generate scenarios based on GARCH models with CTS and RDTS innovations. To investigate the performance of these GARCH models, we report parameter estimates for the Dow Jones Industrial Average index and stocks included in this index. To demonstrate the advantages of the proposed model, we calculate option prices based on the index.     

Settlement delays in the money market

We track 38,000 money market trades from execution to delivery and return, and provide a first empirical analysis of settlement delays in financial markets. In accord with the predictions of recent models of strategic settlement of financial claims, we document a tendency by lenders to delay delivery of loaned funds until the afternoon hours. We find banks to follow a simple strategy to manage the risk of account overdrafts, by delaying settlement of large payments relative to that of small payments. More sophisticated strategies such as increasing delays when own liquid balances are low and when dealing with small trading partners play a marginal role. We find evidence of strategic delay also when returning borrowed funds, although we can explain a smaller fraction of the dispersion in delays in the return than in delivery leg of money market lending.     

FISCAL STIMULUS WITH LEARNING‐BY‐DOING

Using a Bayesian structural vector autoregression analysis, we document that an increase in government purchases raises private consumption, the real wage, and total factor productivity (TFP) while reducing inflation. These three facts are hard to reconcile with both neoclassical and New Keynesian models. We extend a standard New Keynesian model to allow for skill accumulation through past work experience. An increase in government spending increases hours and induces skill accumulation and higher measured TFP and real wages in subsequent periods. Future marginal costs fall lowering expected inflation and, through the monetary policy rule, the real interest rate. Consumption increases as a result.     

Crypto-assets portfolio optimization under the omega measure

Abstract

Crypto-currencies, or crypto-assets, represent a new class of investment assets. The traditional portfolio analysis approach of Markowitz is not appropriate for use with portfolios containing crypto-assets, as the model requires that the investor have a quadratic utility function or that the returns be normally distributed, which isn’t the case for crypto-assets. We develop a portfolio optimization model based on the Omega measure which is more comprehensive than the Markowitz model, and apply this to four crypto-asset investment portfolios by means of a numerical application. The results indicate that these portfolios should favor traditional market assets over crypto-assets. In the case of portfolios formed only by crypto-assets, there is no clear preference in favor of any crypto-asset in particular.     

Relevance of barriers and facilitators in the use of health technology assessment in Colombia

Objectives: Several studies, mostly from developed countries, have identified barriers and facilitators with regard to the uptake of health technology assessment (HTA). This study elicited, using best-worst scaling (BWS), what HTA experts in Colombia consider to be the most important barriers and facilitators in the use of HTA, and makes a comparison to results from the Netherlands.

Methods: Two object case surveys (one for barriers, one for facilitators) were conducted among 18 experts (policymakers, health professionals, PhD students, senior HTA-researchers) from Colombia. Seven respondents were employees of the national HTA agency Instituto de Evaluación Tecnológica de Salud (IETS). In total, 22 barriers and 19 facilitators were included. In each choice task, participants were asked to choose the most and least important barrier/facilitator from a set of five. Hierarchical Bayes modeling was used to compute the mean relative importance scores (RIS) for each factor, and a subgroup analysis was conducted to assess differences between IETS and non-IETS respondents. The final ranking was further compared to the results from a similar study conducted in the Netherlands.

Results: The three most important barriers (RIS >6.00) were “Inadequate presentation format”, “Absence of policy networks”, and “Insufficient legal support”. The six most important facilitators (RIS >6.00) were “Appropriate timing”, “Clear presentation format”, “Improving longstanding relation”, “Appropriate incentives”, “Sufficient qualified human resources”, and “Availability to relevant HTA research”. The perceived relevance of the barriers and facilitators differed slightly between IETS and non-IETS employees, while the differences between the rankings in Colombia and the Netherlands were substantial.

Conclusion: The study suggests that barriers and facilitators related to technical aspects of processing HTA reports and to the contact and interaction between researchers and policymakers had the greatest importance in Colombia.     

Relative forecasting performance of volatility models: Monte Carlo evidence

Abstract

A Monte Carlo (MC) experiment is conducted to study the forecasting performance of a variety of volatility models under alternative data-generating processes (DGPs). The models included in the MC study are the (Fractionally Integrated) Generalized Autoregressive Conditional Heteroskedasticity models ((FI)GARCH), the Stochastic Volatility model (SV), the Long Memory Stochastic Volatility model (LMSV) and the Markov-switching Multifractal model (MSM). The MC study enables us to compare the relative forecasting performance of the models accounting for different characterizations of the latent volatility process: specifications that incorporate short/long memory, autoregressive components, stochastic shocks, Markov-switching and multifractality. Forecasts are evaluated by means of mean squared errors (MSE), mean absolute errors (MAE) and value-at-risk (VaR) diagnostics. Furthermore, complementarities between models are explored via forecast combinations. The results show that (i) the MSM model best forecasts volatility under any other alternative characterization of the latent volatility process and (ii) forecast combinations provide systematic improvements upon most single misspecified models, but are typically inferior to the MSM model even if the latter is applied to data governed by other processes.