Financial market prediction on the basis of online sentiment tracking has drawn a lot of attention recently. However, most results in this emerging domain rely on a unique, particular combination of data sets and sentiment tracking tools. This makes it difficult to disambiguate measurement and instrument effects from factors that are actually involved in the apparent relation between online sentiment and market values. In this paper, we survey a range of online data sets (Twitter feeds, news headlines, and volumes of Google search queries) and sentiment tracking methods (Twitter Investor Sentiment, Negative News Sentiment and Tweet & Google Search volumes of financial terms), and compare their value for financial prediction of market indices such as the Dow Jones Industrial Average, trading volumes, and market volatility (VIX), as well as gold prices. We also compare the predictive power of traditional investor sentiment survey data, i.e. Investor Intelligence and Daily Sentiment Index, against those of the mentioned set of online sentiment indicators. Our results show that traditional surveys of Investor Intelligence are lagging indicators of the financial markets. However, weekly Google Insight Search volumes on financial search queries do have predictive value. An indicator of Twitter Investor Sentiment and the frequency of occurrence of financial terms on Twitter in the previous 1-2 days are also found to be very statistically significant predictors of daily market log return. Survey sentiment indicators are however found not to be statistically significant predictors of financial market values, once we control for all other mood indicators as well as the VIX.
]]>This paper studies the dynamics of stock market volatility and retail investor attention measured by internet search queries. We nd a strong co-movement of stock market indices' realized volatility and the search queries for their names. Furthermore, Granger causality is bi-directional: high searches follow high volatility, and high volatility follows high searches. Using the latter feedback e ect to predict volatility we nd that search queries contain additional information about market volatility. They help to improve volatility forecasts in-sample and out-of-sample as well as for di erent forecasting horizons. Search queries are particularly useful to predict volatility in high-volatility phases.
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The recent boom and bust in commodity prices has raised concerns about the impact of volatile commodity prices on Latin American countries’ fiscal positions. Using a novel quarterly data
set─which includes unique country-specific commodity price indices and a comprehensive measure
of public expenditures─this paper analyzes the dynamic effects of commodity price fluctuations on
fiscal revenues and expenditures for eight commodity-exporting Latin American countries. The
results indicate that Latin American countries’ fiscal positions react strongly to shocks to commodity
prices, yet there are marked differences across countries. Fiscal variables in Venezuela display the
highest sensitivity to commodity price shocks, with expenditures reacting significantly more than
revenues. At the other end of the spectrum, in Chile expenditure reacts very little to commodity price
fluctuations, and the dynamic responses of its fiscal indicators are very similar to those seen in highincome commodity-exporting countries. This distinct behavior across countries may relate to
institutional arrangements, which in some cases include the efficient application of fiscal rules amid
political commitment and high standards of transparency.
The purpose of this article is to identify the role of population size, population growth and population ageing in models of endogenous economic growth. While in exogenous growth models demographic variables are linked to economic prosperity mainly via the population size, the structure of the workforce, and the capital intensity of workers, endogenous growth models and their successors also allow for interrelationships between demography and technological change. However, most of the existing literature considers only the interrelationships based on population size and its growth rate and does not explicitly account for population ageing. The aim of this paper is (a) to review the role of population size and
population growth in the most commonly used economic growth models (with a focus on endogenous economic growth models), (b) discuss models that also allow for population ageing, and (c) sketch out the policy implications of the most commonly used endogenous growth models and compare them to each other.
This paper attempts to examine the relationship between health and economic growth. The rate of growth is measured using gross national income (GNI) and health status is measured using infant mortality rate, life expectancy rate and crude health rate. The above relationships are measured using a multivariate framework controlling for other background variables. Thus we have modelled the macroeconomic impact of health. A theoretical framework has been developed to model this linkage between health and growth and this is further tested using a regression model which tests the causality between these variables of interest. These models are tested using pooled data. We have also assumed in this analysis that these variables are affected by state-specific unobservable fixed effects, since there are other cultural, political and social factors at work here.
]]>This paper shows that, controlling for standard determinants of net external positions, financially-remote countries exhibit more positive net external positions. This finding is found to be stronger for less advanced countries, hinting at external funding problems formore remote countries. Being located near financially very open countries, being in currency unions with creditor countries, or being highly integrated through financial and trade linkages with a ‘core’ country facilitates net external borrowing. Consequently, evidence is found for an important role of geographic and bilateral factors for a country’s net external wealth.
]]>Homeownership affects investment, consumption, and savings decisions of households, and plays a major role in post-retirement well-being. This paper examines two questions. First, to what extent do Canadians acquire and retain homeownership at different life-course stages, particularly after retirement? Second, has the age profile of homeownership changed over generations?
Using data from eight Canadian censuses of population, conducted between 1971 and 2006, we find a strong regularity in the age profile of homeownership across generations of Canadians. The homeownership rate rises quickly with the age of household maintainers (i.e., the person(s) who pay(s) for shelter costs) in the period before the age of 40, and continues to climb thereafter at a slower pace until reaching the plateau near age 65, when about three quarters of Canadian households own their homes. We find that the homeownership rate changes little from age 65 to 74 but starts declining after age 75. As well, we note that the level at which homeownership plateaus has risen steadily across birth cohorts since the 1970s.
]]>As an asset is traded, its varying prices trace out an interesting time series. The price, at least in a general way, rejects some underlying value of the asset. For most basic assets, realistic models of value must involve many variables relating not only to the individual asset, but also to the asset class, the industrial sector(s) of the asset, and both the local economy and the general global economic conditions. Rather than attempting to model the value, we will con ne our interest to modeling the price. The underlying assumption is that the price at which an asset trades is a "fair market price" that rejects the actual value of the asset. Our initial interest is in models of the price of a basic asset, that is, not the price of a derivative asset. Usually instead of the price itself, we consider the relative change in price, that is, the rate of return, over some interval of time.
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Age structured populations are studied in economics through overlapping generations models. These models allow for a realistic characterization of life-cycle behaviors and display intertemporal equilibrium
that are not necessarily efficient. This article uses the latest developments in continuous time overlapping generations models to show the influence of the vintage structure of the population on the volatility of intertemporal prices. Permanent cycles can be found on the neighborhood
of steady-states while the transitional dynamics are generically governed by short run fluctuations.