Investment behaviour and “bull & bear” dynamics: modelling real and stock market interactions

In this article, we develop a simple behavioural macrodynamic model in continuous-time with the purpose of investigating the interaction of the real economy and the financial markets. Building on Westerhoff (Discret Dyn Nat Soc, 2012), we improve the specification of aggregate demand by distinguishing between consumption and investment expenditure and assuming that the latter is determined by the flexible accelerator principle. We remove the ad hoc nonlinearity in the fundamentalist behavioural rule and allow the composition of the population between chartists and fundamentalists to be endogenously determined. The resulting nonlinear dynamic systems are shown to generate various dynamic regimes, among which the coexistence of periodic attractors with interesting economic implications. Endogenous investment and stock market dynamics emerge, procyclical to each other, reflecting the interaction of induced investment with alternating waves in speculators’ sentiments. We show that a strong investment accelerator might be a crucial force generating fluctuations that, on the one hand, are transmitted and amplified by chartists and, on the other hand, are contained by fundamentalists.

     

Macroeconomic Volatility,Institutional Instability and the Incentive to Innovate

This study investigates the channels through which macroeconomic and institutional instability hinders innovative investment undertakings financed by the domestic private sector. The analysis is based on a sample of 44 countries and considers various instability dimensions. The results suggest a negative impact of real, monetary and political instability on the aggregate level of R&D financed by the business sector. Thus, highlighting the importance of stable macro‐institutional environments in preventing avoidance or abandonment of private innovation undertakings.     

A Hedonic Analysis of Nutrition and Health Claims on Fruit Beverage Products

This paper investigates the effects on prices of nutrition and health claims for foodstuffs, in addition to other attributes, using fruit beverages as a case study. The model estimation is based on revealed purchasing behaviour for fruit beverages in the north‐east of Italy. Applying an hedonic price model, the price of a product is explained as a function of product attributes. The model estimate identifies the implicit retail‐market‐level price of specific attributes such as nutrition and health claims, ceteris paribus. Nutrition and health claims significantly affect retail prices. Our findings suggest that retail price response to nutrition and health claims differs in relation to other product attributes, showing a strong reduction of price variation among flavours when such benefits are claimed on the label.     

Non‐Standard Time Wage Premiums and Employment Effects: Evidence from an Australian Natural Experiment

We examine the effect of increasing Sunday wage premiums on retail industry employment in Australia, exploiting a quasi‐experimental policy change across two neighbouring states. Using both aggregate and individual‐level data, we adopt a difference‐in‐difference regression framework to estimate the causal impact of the policy change on employment outcomes. We find no evidence of changes in the total number of employees, and no effect on hours per employee in the years following the policy implementation. However, there appeared to be a decline in hours per employee in the announcement year of the policy change. Overall, it appears that in an industry dominated by part‐time and casual employment, any adjustment to the new Sunday wage rates occurred principally through flexibility in hours, rather than in the number of employees.     

Measuring innovation in services: the role of surveys

The main aim of this paper was to analyse the role of European innovation surveys in measuring innovation in services. The various community innovation surveys (CISs) are analysed in the light of the three main theoretical approaches to innovation in services, namely assimilation, service-oriented and integrative. The analysis performed shows a gradual change in the way in which European surveys have been structured over time, highlighting a partial shift from the assimilation approach towards the integrative one. Furthermore, the paper provides a systematic assessment of the CIS experience and of the lessons to be drawn from it.     

Principal components estimation and identification of static factors

It is known that the principal component estimates of the factors and the loadings are rotations of the underlying latent factors and loadings. We study conditions under which the latent factors can be estimated asymptotically without rotation. We derive the limiting distributions for the estimated factors and factor loadings when N$N$ and T$T$ are large and make precise how identification of the factors affects inference based on factor augmented regressions. We also consider factor models with additive individual and time effects. The asymptotic analysis can be modified to analyze identification schemes not considered in this analysis.     

Capturing how individuals perceive genetic risk information: a phenomenological perspective

The prevailing scientific approach to genetic risk information centres around communication of risk in terms of numerical probabilities. However, it is well known that individuals have difficulties in understanding and making sense of this information in their own lives. There is, accordingly, a need to investigate whether any methodologies in psychological research may shed light on how individuals perceive genetic risk information within their specific contexts of family history, personal relationships, lifestyles and future plans. To explore whether hermeneutic phenomenology and methodology may offer a deeper understanding of an individual’s perception of having a hereditary predisposition, we conducted a literature search. We found that Interpretative Phenomenological Analysis may be a fruitful approach to an individual’s lived experiential world. The studies analysed showed how individuals interpret information about genetic risk in the light of their own beliefs about the multiple causes of illness, patterns of heredity and observable risk factors in their families. People’s understanding of their experience is derived from an intricate interconnectedness with others that arises in the context of a world shaped in equal measure by language and culture, on the one hand, and bodies and objects on the other.     

Reserves,Sovereign Wealth Funds and the Resilience of Global Imbalances

Reserves and sovereign wealth funds (SWFs) assets should be jointly considered for the assessment of global imbalances, hence their denomination as sovereign external assets (SEAs): both are public capital outflows from developing to developed countries, both hinder adjustment in current account surplus and deficit countries and, therefore, both contribute to sustain global imbalances. They represented 135 per cent and 50 per cent of net and gross US financing needs, respectively, in 2007. Reserves contribute 80 per cent and SWFs 20 per cent. They will go on providing resilience to the global imbalances, and the relative importance of SWFs is set to increase if commodity prices stay high.     

The empirical risk–return relation: A factor analysis approach

Existing empirical literature on the risk–return relation uses relatively small amount of conditioning information to model the conditional mean and conditional volatility of excess stock market returns. We use dynamic factor analysis for large data sets, to summarize a large amount of economic information by few estimated factors, and find that three new factors—termed “volatility,” “risk premium,” and “real” factors—contain important information about one-quarter-ahead excess returns and volatility not contained in commonly used predictor variables. Our specifications predict 16–20% of the one-quarter-ahead variation in excess stock market returns, and exhibit stable and statistically significant out-of-sample forecasting power. We also find a positive conditional risk–return correlation.