Assessing the impact of co-branding of island destination and tourism activities on tourists’ reactions

The aim of this study is to examine the status and images of certain islands based on specific tourism activities. A total of 385 valid samples were obtained from tourists at the islands' main transportation facilities. The results are as follows: (1) different island destinations are promoted differently, which significantly affects the perceptions of tourists. (2) Tourists' familiarity with various tourism activities and the rate of participation in these activities vary significantly between the islands; in addition, tourists display greater familiarity with beach/water activities and participate in these activities in higher proportions. (3) Greater consistency in the matching of island destinations with tourism activities helps produce a co-branding effect, which positively affects tourists' perception of these destinations. From a co-branding perspective, this study demonstrates that the empirical market positioning of island destinations must be consistent with the tourism activities that are possible to produce an optimal experience for the tourists. This comparison of different islands explains why the development of island tourism on such locations should involve the provision of information on rankings and tourism activities.     

Fixed investment,factor substitution and the elasticity of demand

The results of comparative stability analysis of demand- and supply-side input–output models using the UK data are presented, as well as the results of the comparison between the UK and US comparative stability analyses of the two models. The results of comparative stability analysis of the two models using the US data were reported elsewhere (Bon, 1986). The forecasts of sectoral and total output of the two models are generated with known final demand and value added figures from subsequent tables, and are compared with known output figures for benchmark years. The results of the UK and US studies are very similar. The demand-side model performs somewhat better in terms of total output forecasts, but the supply-side model performs some-what better for a larger number of sectors. In particular, the supply-side model offers better forecasts for the mature economic sectors such as agriculture, mining, and construction. Both models should be used to determine the extent to which an extent to which an economy or a sector are demand- or supply-driven.     

Politics vs Economics: Evidence from Municipal Annexation

This paper investigates economic and political factors in suburban annexation decision in large U.S. cities. This paper employs a median-voter model, which suggests a natural latent-variable estimation strategy. Bivariate logit and normal procedures incorporating information about state laws governing annexation are run on census tract level data. Estimated parameters are used to evaluate the effects of economic and political variables. Results show cities' desire to expropriate suburban tax base did not motivate annexation, although cities were sensitive to other economic factors. The desire to offset political and racial effects of urban migration had a consistent and positive effect on annexation.     

Income inequality,volatility, and mobility risk in China and the US

A unified index of income inequality, volatility, and mobility risk is presented, and measurements based on US and Chinese panel data calculated. China is found to have higher-income volatility than the US in recent data, so that long-run inequality is comparable in the two countries, and short-run inequality overstates long-run inequality more in China than in the US. In both countries volatility and income inequality are increasing over time.     

How efficiency shapes market impact

We develop a theory for the market impact of large trading orders, which we call metaorders because they are typically split into small pieces and executed incrementally. Market impact is empirically observed to be a concave function of metaorder size, i.e. the impact per share of large metaorders is smaller than that of small metaorders. We formulate a stylized model of an algorithmic execution service and derive a fair pricing condition, which says that the average transaction price of the metaorder is equal to the price after trading is completed. We show that at equilibrium the distribution of trading volume adjusts to reflect information, and dictates the shape of the impact function. The resulting theory makes empirically testable predictions for the functional form of both the temporary and permanent components of market impact. Based on the commonly observed asymptotic distribution for the volume of large trades, it says that market impact should increase asymptotically roughly as the square root of metaorder size, with average permanent impact relaxing to about two-thirds of peak impact.