The Importance of Graduates for the Scottish Economy: A “Micro-to-Macro” Approach

There have been numerous attempts to assess the overall impact of Higher Education Institutions on regional economies in the UK and elsewhere. There are two disparate approaches focussing on: demand-side effects of HEIs, exerted through universities’ expenditures within the local economy; HEIs’ contribution to the “knowledge economy”. However, neither approach seeks to measure the impact on regional economies that HEIs exert through the enhanced productivity of their graduates. We address this lacuna and explore the system-wide impact of the graduates on the regional economy. An extensive and sophisticated literature suggests that graduates enjoy a significant wage premium, often interpreted as reflecting their greater productivity relative to non-graduates. If this is so there is a clear and direct supply-side impact of HEI activities on regional economies through the employment of their graduates. However, there is some dispute over the extent to which the graduate wage premium reflects innate abilities rather than the impact of higher education per se. We use an HEI-disaggregated computable general equilibrium model of Scotland to estimate the impact of the growing proportion of graduates in the Scottish labour force that is implied by the current participation rate and demographic change, taking the graduate wage premium in Scotland as an indicator of productivity enhancement. We conduct a range of sensitivity analyses to assess the robustness of our results. While the detailed results do, of course, vary with alternative assumptions about future graduate retention rates and the size of the graduate wage premium, for example, they do suggest that the long-term supply-side impacts of HEIs provide a significant boost to regional GDP. Furthermore, the results suggest that the supply-side impacts of HEIs are likely to be more important than the expenditure impacts that are the focus of most “impact” studies.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

A New Model Of Trend Inflation

This paper introduces a new model of trend (or underlying) inflation. In contrast to many earlier approaches, which allow for trend inflation to evolve according to a random walk, ours is a bounded model which ensures that trend inflation is constrained to lie in an interval. The bounds of this interval can either be fixed or estimated from the data. Our model also allows for a time-varying degree of persistence in the transitory component of inflation. The bounds placed on trend inflation mean that standard econometric methods for estimating linear Gaussian state space models cannot be used and we develop a posterior simulation algorithm for estimating the bounded trend inflation model. In an empirical exercise with CPI inflation we find the model to work well, yielding more sensible measures of trend inflation and forecasting better than popular alternatives such as the unobserved components stochastic volatility model.

The system-wide impacts of the external benefits to higher education on the Scottish economy: An exploratory “micro-to-macro” approach

The private market benefits of education, i.e. the wage premia of graduates, are widely studied at the micro level, although the magnitude of their macroeconomic impact is disputed. However, there are additional benefits of education, which are less well understood but could potentially drive significant macroeconomic impacts. Following the taxonomy of McMahon (2009) we identify four different types of benefits of education. These are: private market benefits (wage premia); private non market benefits (own health, happiness, etc.); external market benefits (productivity spillovers; and external non-market benefits (crime rates, civic society, democratisation, etc.). Drawing on available microeconometric evidence we use a micro-to-macro simulation approach (Hermannsson et al, 2010) to estimate the macroeconomic impacts of external benefits of higher education. We explore four cases: technology spillovers from HEIs; productivity spillovers from more skilled workers in the labour market; reduction in property crime; and the potential overall impact of external and private non-market benefits. Our results suggest that the external economic benefits of higher education could potentially be very large. However, given the dearth of microeconomic evidence this result should be seen as tentative. Our aim is to illustrate the links from education to the wider economy in principle and encourage further research in the field.

The Impact of Population Ageing on the Labour Market: Evidence from Overlapping Generations Computable General Equilibrium (OLG-CGE) Model of Scotland

This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.

Growth and Survival Determinants of Chinese Private Firms: Fieldwork evidence and econometric estimates

This paper reports on one of the first empirical attempts to investigate small firm growth and survival, and their determinants, in the Peoples’ Republic of China. The work is based on field work evidence gathered from a sample of 83 Chinese private firms (mainly SMEs) collected initially by face-to-face interviews, and subsequently by follow-up telephone interviews a year later. We extend the models of Gibrat (1931) and Jovanovic (1982), which traditionally focus on size and age alone (e.g. Brock and Evans, 1986), to a ‘comprehensive’ growth model with two types of additional explanatory variables: firm-specific (e.g. business planning); and environmental (e.g. choice of location). We estimate two econometric models: a ‘basic’ age-size-growth model; and a ‘comprehensive’ growth model, using Heckman’s two-step regression procedure. Estimation is by log-linear regression on cross-section data, with corrections for sample selection bias and heteroskedasticity. Our results refute a pure Gibrat model (but support a more general variant) and support the learning model, as regards the consequences of size and age for growth; and our extension to a comprehensive model highlights the importance of location choice and customer orientation for the growth of Chinese private firms. In the latter model, growth is explained by variables like planning, R&D orientation, market competition, elasticity of demand etc. as well as by control variables. Our work on small firm growth achieves two things. First, it upholds the validity of ‘basic’ size-age-growth models, and successfully applies them to the Chinese economy. Second, it extends the compass of such models to a ‘comprehensive’ growth model incorporating firm-specific and environmental variables.

The Impact of Population Ageing on the Labour Market: Evidence from Overlapping Generations Computable General Equilibrium (OLG-CGE) Model of Scotland

This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.

Human Capital in Economic Development: From Labour Productivity to Macroeconomic Impact

Micro-econometric evidence reveals high private returns to education, most prominently in low-income countries. However, it is disputed to what extent this translates into a macro-economic impact. This paper projects the increase in human capital from higher education in Malawi and uses a dynamic applied general equilibrium model to estimate the resulting macroeconomics impact. This is contingent upon endogenous adjustments, in particular how labour productivity affects competitiveness and if this in turn stimulates exports. Choice among commonly applied labour market assumptions and trade elasticities results in widely different outcomes. Appraisal of such policies should consider not only the impact on human capital stocks, but also adjustments outside the labour market.

Macroeconomics of extensive margins: a simple model

How do monopolistically competitive industries react to shocks in the context of a New Keynesian macro model? I bridge macroeconomics and trade theory by considering market dynamics. I use an analytically tractable closed-economy model with endogenous entry of firms and show the implications of markets structure for the transmission of real shocks on aggregate variables and welfare. Shock sources become crucial for the results: traditional productivity shocks cause an extensive effect on production; shocks on innovation cause an intensive impact. More patient populations bring the economy to a richer market, although it cushions the extensive effect after an innovation shock.

How to use the standard model with own data?

In this work discuss the use of the standard model for the calculation of the solvency capital requirement (SCR) when the company aims to use the specific parameters of the model on the basis of the experience of its portfolio. In particular, this analysis focuses on the formula presented in the latest quantitative impact study (2010 CEIOPS) for non-life underwriting premium and reserve risk. One of the keys of the standard model for premium and reserves risk is the correlation matrix between lines of business. In this work we present how the correlation matrix between lines of business could be estimated from a quantitative perspective, as well as the possibility of using a credibility model for the estimation of the matrix of correlation between lines of business that merge qualitative and quantitative perspective.

Inflation dynamics: A structural econometric analysis

We develop and estimate a structural model of inflation that allowsfor a fraction of firms that use a backward looking rule to setprices. The model nests the purely forward looking New KeynesianPhillips curve as a particular case. We use measures of marginalcosts as the relevant determinant of inflation, as the theorysuggests, instead of an ad-hoc output gap. Real marginal costsare a significant and quantitatively important determinant ofinflation. Backward looking price setting, while statisticallysignificant, is not quantitatively important. Thus, we concludethat the New Keynesian Phillips curve provides a good firstapproximation to the dynamics of inflation.

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

Inflammatory response in a rat model of gastroschisis is associated with an increase of NF-kappaB

Babies with gastroschisis have high morbidity, which is associated with inflammatory bowel injury caused by exposure to amniotic fluid. The objective of this study was to identify components of the inflammatory response in the intestine and liver in an experimental model of gastroschisis in rats. The model was surgically created at 18.5 days of gestation. The fetuses were exposed through a hysterotomy and an incision at the right of the umbilicus was made, exposing the fetal bowel. Then, the fetus was placed back into the uterus until term. The bowel in this model had macro- and microscopic characteristics similar to those observed in gastroschisis. The study was conducted on three groups of 20 fetuses each: gastroschisis, control, and sham fetuses. Fetal body, intestine and liver weights and intestine length were measured. IL-1β, IL-6, IL-10, TNF-α, IFN-γ and NF-kappaB levels were assessed by ELISA. Data were analyzed statistically by ANOVA followed by the Tukey post-test. Gastroschisis fetuses had a decreased intestine length (means ± SD, 125 ± 25 vs 216 ± 13.9; P < 0.005) and increased intestine weight (0.29 ± 0.05 vs 0.24 ± 0.04; P < 0.005). Intestine length correlated with liver weight only in gastroschisis fetuses (Pearson’s correlation coefficient, r = 0.518, P = 0.019). There were no significant differences in the concentrations of IL-1β, TNF-α or IFN-γ in the intestine, whereas the concentration of NF-kappaB was increased in both the intestine and liver of fetuses with gastroschisis. These results show that the inflammatory response in the liver and intestine of the rat model of gastroschisis is accompanied by an increase in the amount of NF-kappaB in the intestine and liver.

The Forecast Performance of Model-Free Implied Volatility: Evidence from DAX Index Options

Volatility has a central role in various theoretical and practical applications in financial markets. These include the applications related to portfolio theory, derivatives pricing and financial risk management. Both theoretical and practical applications require good estimates and forecasts for the asset return volatility. The goal of this study is to examine the forecast performance of one of the more recent volatility measures, model-free implied volatility. Model-free implied volatility is extracted from the prices in the option markets, and it aims to provide an unbiased estimate for the market’s expectation on the future level of volatility. Since it is extracted from the option prices, model-free implied volatility should contain all the relevant information that the market participants have. Moreover, model-free implied volatility requires less restrictive assumptions than the commonly used Black-Scholes implied volatility, which means that it should be less biased estimate for the market’s expectations. Therefore, it should also be a better forecast for the future volatility. The forecast performance of model-free implied volatility is evaluated by comparing it to the forecast performance of Black-Scholes implied volatility and GARCH(1,1) forecast. Weekly forecasts for six years period were calculated for the forecasted variable, German stock market index DAX. The data consisted of price observations for DAX index options. The forecast performance was measured using econometric methods, which aimed to capture the biasedness, accuracy and the information content of the forecasts. The results of the study suggest that the forecast performance of model-free implied volatility is superior to forecast performance of GARCH(1,1) forecast. However, the results also suggest that the forecast performance of model-free implied volatility is not as good as the forecast performance of Black-Scholes implied volatility, which is against the hypotheses based on theory. The results of this study are consistent with the majority of prior research on the subject.