Northeast : 1984 population and 1983 per capita income estimates for counties and incorporated places.

"Issued June 1986."

Northeast : 1986 population and 1985 per capita income estimates for counties and incorporated places.

Errata page inserted.

West : 1986 population and 1985 per capita income estimates for counties and incorporated places.

Errata page inserted.

West North Central : 1988 population and 1987 per capita income estimates for counties and incorporated places.

"Issued March 1990."

South : 1986 population and 1985 per capita income estimates for counties and incorporated places.

Errata page inserted.

The Illinois economic model : phase I /

"December, 1977."

Uniform economic/demographic projections, 1970-2000 /

Prepared by David E. Scoville, and others.

Lifetime earnings estimates for men and women in the United States, 1979.

Mode of access: Internet.

Forecasting individual income tax revenues : a technical analysis.

Mode of access: Internet.

The role of income inequality on fiscal multipliers

A Work Project, presented as part of the requirements for the Award of a Masters Double Degree in Economics from the Nova School of Business and Economics and University of Maastricht

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Data uncertainty in real estate forecasting

The rapid expansion of the TMT sector in the late 1990s and more recent growing regulatory and corporate focus on business continuity and security have raised the profile of data centres. Data centres offer a unique blend of occupational, physical and technological characteristics compared to conventional real estate assets. Limited trading and heterogeneity of data centres also causes higher levels of appraisal uncertainty. In practice, the application of conventional discounted cash flow approaches requires information about a wide range of inputs that is difficult to derive from limited market signals or estimate analytically. This paper outlines an approach that uses pricing signals from similar traded cash flows is proposed. Based upon ‘the law of one price’, the method draws upon the premise that two identical future cash flows must have the same value now. Given the difficulties of estimating exit values, an alternative is that the expected cash flows of data centre are analysed over the life cycle of the building, with corporate bond yields used to provide a proxy for the appropriate discount rates for lease income. Since liabilities are quite diverse, a number of proxies are suggested as discount and capitalisation rates including indexed-linked, fixed interest and zero-coupon bonds. Although there are rarely assets that have identical cash flows and some approximation is necessary, the level of appraiser subjectivity is dramatically reduced.

Modeling and forecasting long-term natural gas (NG) consumption in Iran, using particle swarm optimization (PSO)

The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

The role of no-arbitrage on forecasting: lessons from a parametric term structure model

Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.

The influence of materialism on consumption indebtedness in the context of low income consumers from the city of São Paulo

This research is in the domains of materialism, consumer vulnerability and consumption indebtedness, concepts frequently approached in the literature on consumer behavior, macro-marketing and economic psychology. The influence of materialism on consumer indebtedness is investigated within a context that is characterized by poverty and by factors that cause vulnerability, such as high interest rates, limited access to credit and to quality affordable goods. The objectives of this research are: to produce a materialism scale that is well adapted to its environment, characterizing materialism adequately for the population studied; to compare results obtained with results of other studies; and to measure the relationship between materialism, socio-demographic variables, attitude to debt and consumption indebtedness. The primary data used in the analyses were collected from field research carried out in August, 2005 that relied on a probabilistic household sample of 450 low income individuals who live in poor regions of the city of Sao Paulo. The materialism scale, adapted and translated into Portuguese from Richins (2004), proved to be very successful and encourages new work in the area. It was noted that younger adults tend to be more materialistic than older ones; that illiterate adults tend to be less materialistic than those who did literacy courses when they were already adults; and that gender, income and race are not associated with the materialism construct. Among the other results, a logistic regression model was developed in order to distinguish those individuals who have an installment plan payment booklet from those who do not, based on materialism, socio-demographic variables and purchasing and consumer habits. The proposed model confirms materialism as a behavioral variable useful for forecasting the probability of an individual getting into debt in order to consume, in some cases almost doubling the chance of occurrence of this event. Findings confirm the thesis that it is not only adverse economic factors that lead people to get into debt; and that the study of demand for credit for consumption purposes must, of necessity, include variables of a psychological nature. It is suggested that the low income materialistic consumer experiences feelings of powerlessness and exclusion because of the gap that exists between their possessions and their desires. Lines of conduct to combat this marginalization from the consumer society are drawn targeting marketing professionals, public policy makers and vulnerability researchers. Finally, the possibility of new studies involving the materialism construct, which is central to literature on consumer behavior, albeit little used in empirical studies in Brazil, are discussed.