The Changing Structure of Arkansas\u27 Economy: A Shift-Share Analysis

The state of Arkansas enjoys the advantages of its unique central location in the nation, excellent natural surroundings, low cost of living, and one of the best business climates in the southern United States. It is home to several of the largest corporations in the world. Over the period 1980-2000, there was tremendous growth in the state’s economy. However, the growth was confined to specific regions that led to several socio-economic issues adversely affecting the state. To better understand the components and variations in economic growth, a county-wise shift-share analysis was conducted. Employment, a good indicator of economic growth, was used to analyze the changes in the local economic structure of the 75 counties in the state. Findings suggest that while services and retail trade continue to grow, manufacturing and the state/local government continue to be important employers for the state. Farm employment continues to decline, although farm-related manufacturing and services are becoming more important. This report provides a sectoral analysis of employment changes within the counties and is a potential point of reference for both government and industry engaged in community-level policy making and investment

Is Attracting Retirees a Sustainable Rural Economic Development Policy?

An economic impact analysis was conducted in two rural counties in Northwest Arkansas to observe effects of hypothetical retiree in-migration as a sustainable economic development policy. The analysis reveals economic benefits with varying impacts and additional socio-economic costs on both counties. The policy has the potential for sustaining in the long-term.Community/Rural/Urban Development,

Mental state estimation for brain-computer interfaces

Mental state estimation is potentially useful for the development of asynchronous brain-computer interfaces. In this study, four mental states have been identified and decoded from the electrocorticograms (ECoGs) of six epileptic patients, engaged in a memory reach task. A novel signal analysis technique has been applied to high-dimensional, statistically sparse ECoGs recorded by a large number of electrodes. The strength of the proposed technique lies in its ability to jointly extract spatial and temporal patterns, responsible for encoding mental state differences. As such, the technique offers a systematic way of analyzing the spatiotemporal aspects of brain information processing and may be applicable to a wide range of spatiotemporal neurophysiological signals

How CMB and large-scale structure constrain chameleon interacting dark energy

We explore a chameleon type of interacting dark matter-dark energy scenario in which a scalar field adiabatically traces the minimum of an effective potential sourced by the dark matter density. We discuss extensively the effect of this coupling on cosmological observables, especially the parameter degeneracies expected to arise between the model parameters and other cosmological parameters, and then test the model against observations of the cosmic microwave background (CMB) anisotropies and other cosmological probes. We find that the chameleon parameters $\alpha$ and $\beta$, which determine respectively the slope of the scalar field potential and the dark matter-dark energy coupling strength, can be constrained to $\alpha < 0.17$ and $\beta < 0.19$ using CMB data alone. The latter parameter in particular is constrained only by the late Integrated Sachs-Wolfe effect. Adding measurements of the local Hubble expansion rate $H_0$ tightens the bound on $\alpha$ by a factor of two, although this apparent improvement is arguably an artefact of the tension between the local measurement and the $H_0$ value inferred from Planck data in the minimal $\Lambda$CDM model. The same argument also precludes chameleon models from mimicking a dark radiation component, despite a passing similarity between the two scenarios in that they both delay the epoch of matter-radiation equality. Based on the derived parameter constraints, we discuss possible signatures of the model for ongoing and future large-scale structure surveys.Comment: 25 pages, 6 figure

Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction

When correcting for biases in general circulation model (GCM) output, for example when statistically downscaling for regional and local impacts studies, a common assumption is that the GCM biases can be characterized by comparing model simulations and observations for a historical period. We demonstrate some complications in this assumption, with GCM biases varying between mean and extreme values and for different sets of historical years. Daily precipitation and maximum and minimum temperature from late 20th century simulations by four GCMs over the United States were compared to gridded observations. Using random years from the historical record we select a base set and a 10 yr independent projected set. We compare differences in biases between these sets at median and extreme percentiles. On average a base set with as few as 4 randomly-selected years is often adequate to characterize the biases in daily GCM precipitation and temperature, at both median and extreme values; 12 yr provided higher confidence that bias correction would be successful. This suggests that some of the GCM bias is time invariant. When characterizing bias with a set of consecutive years, the set must be long enough to accommodate regional low frequency variability, since the bias also exhibits this variability. Newer climate models included in the Intergovernmental Panel on Climate Change fifth assessment will allow extending this study for a longer observational period and to finer scales

Distributional Impacts of Agritourism in the Arkansas Delta Byways region

Replaced with revised version of paper 06/16/09.ARIMA, Agritourism Demand, Economic Impact Analysis, Rural Economic Development, Agribusiness, Community/Rural/Urban Development, R15, R58,

Spatial Variability of Tourism Demand and Differences in Economic Impact in a Rural Economic Development Context

Statistically predicted future tourism demand is used to conduct an economic impact analysis in twelve tourism zones in the state of Arkansas. The analysis reveals spatial variability in employment, and output growth that will continue into the future. Tourism has the potential as an economic growth engine for the state, especially in economically disadvantaged regions with long-term benefits.Tourism Demand, Economic Impact Analysis, Rural Development, Community/Rural/Urban Development, Resource /Energy Economics and Policy, R15, R58,