Using Leading Indicators to Forecast US Home Sales in a Bayesian VAR Framework

This paper uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting US home sales. The benchmark Bayesian model includes home sales, the price of homes, the mortgage rate, real personal disposable income, and the unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

ECONOMIC ANALYSIS OF THE DEMAND FOR PRESCRIPTION MEDICINE IN THE UNITED STATES

The purpose of this study was to understand the role of principle economic, sociodemographic and health status factors in determining the likelihood and volume of prescription drug use. Econometric demand regression models were developed for this purpose. Ten explanatory variables were examined: family income, coinsurance rate, age, sex, race, household head education level, size of family, health status, number of medical visits, and type of provider seen during medical visits. The economic factors (family income and coinsurance) were given special emphasis in this study.^ The National Medical Care Utilization and Expenditure Survey (NMCUES) was the data source. The sample represented the civilian, noninstitutionalized residents of the United States in 1980. The sample method used in the survey was a stratified four-stage, area probability design. The sample was comprised of 6,600 households (17,123 individuals). The weighted sample provided the population estimates used in the analysis. Five repeated interviews were conducted with each household. The household survey provided detailed information on the United States health status, pattern of health care utilization, charges for services received, and methods of payments for 1980.^ The study provided evidence that economic factors influenced the use of prescription drugs, but the use was not highly responsive to family income and coinsurance for the levels examined. The elasticities for family income ranged from -.0002 to -.013 and coinsurance ranged from -.174 to -.108. Income has a greater influence on the likelihood of prescription drug use, and coinsurance rates had an impact on the amount spent on prescription drugs. The coinsurance effect was not examined for the likelihood of drug use due to limitations in the measurement of coinsurance. Health status appeared to overwhelm any effects which may be attributed to family income or coinsurance. The likelihood of prescription drug use was highly dependent on visits to medical providers. The volume of prescription drug use was highly dependent on the health status, age, and whether or not the individual saw a general practitioner. ^

TECHNOLOGY ASSESSMENT: SMALL-VOLUME INFUSION PUMPS

"Technology assessment is a comprehensive form of policy research that examines the short- and long-term social consequences of the application or use of technology" (US Congress 1967).^ This study explored a research methodology appropriate for technology assessment (TA) within the health industry. The case studied was utilization of external Small-Volume Infusion Pumps (SVIP) at a cancer treatment and research center. Primary and secondary data were collected in three project phases. In Phase I, hospital prescription records (N = 14,979) represented SVIP adoption and utilization for the years 1982-1984. The Candidate Adoption-Use (CA-U) diffusion paradigm developed for this study was germane. Compared to classic and unorthodox curves, CA-U more accurately simulated empiric experience. The hospital SVIP 1983-1984 trends denoted assurance in prescribing chemotherapy and concomitant balloon SVIP efficacy and efficiency. Abandonment of battery pumps was predicted while exponential demand for balloon SVIP was forecast for 1985-1987. In Phase II, patients using SVIP (N = 117) were prospectively surveyed from July to October 1984; the data represented a single episode of therapy. The questionnaire and indices, specifically designed to measure the impact of SVIP, evinced face validity. Compeer group data were from pre-SVIP case reviews rather than from an inpatient sample. Statistically significant results indicated that outpatients using SVIP interacted socially more than inpatients using the alternative technology. Additionally, the hospital's education program effectively taught clients to discriminate between self care and professional SVIP services. In these contexts, there was sufficient evidence that the alternative technology restricted patients activity whereas SVIP permitted patients to function more independently and in a social lifestyle, thus adding quality to life. In Phase III, diffusion forecast and patient survey findings were combined with direct observation of clinic services to profile some economic dimensions of SVIP. These three project phases provide a foundation for executing: (1) cost effectiveness analysis of external versus internal infusors, (2) institutional resource allocation, and (3) technology deployment to epidemiology-significant communities. The models and methods tested in this research of clinical technology assessment are innovative and do assess biotechnology. ^

PRETERM BIRTH AND OCCUPATIONAL PHYSICAL ACTIVITY: A CASE-CONTROL STUDY OF THE RELATIONSHIP BETWEEN LENGTH OF GESTATION AND THE PHYSICAL DEMAND OF U.S. ARMY MILITARY OCCUPATIONAL SPECIALTIES (UNITED STATES)

A case-control study has been conducted examining the relationship between preterm birth and occupational physical activity among U.S. Army enlisted gravidas from 1981 to 1984. The study includes 604 cases (37 or less weeks gestation) and 6,070 controls (greater than 37 weeks gestation) treated at U.S. Army medical treatment facilities worldwide. Occupational physical activity was measured using existing physical demand ratings of military occupational specialties.^ A statistically significant trend of preterm birth with increasing physical demand level was found (p = 0.0056). The relative risk point estimates for the two highest physical demand categories were statistically significant, RR's = 1.69 (p = 0.02) and 1.75 (p = 0.01), respectively. Six of eleven additional variables were also statistically significant predictors of preterm birth: age (less than 20), race (non-white), marital status (single, never married), paygrade (E1 - E3), length of military service (less than 2 years), and aptitude score (less than 100).^ Multivariate analyses using the logistic model resulted in three statistically significant risk factors for preterm birth: occupational physical demand; lower paygrade; and non-white race. Controlling for race and paygrade, the two highest physical demand categories were again statistically significant with relative risk point estimates of 1.56 and 1.70, respectively. The population attributable risk for military occupational physical demand was 26%, adjusted for paygrade and race; 17.5% of the preterm births were attributable to the two highest physical demand categories. ^

PROJECTION OF HEALTH DEMAND IN TERMS OF HOSPITAL ADMISSIONS FOR SELECTED DIAGNOSES IN HEALTH SYSTEMS AGENCY SERVICE AREAS

The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^

AN ECONOMIC ANALYSIS OF THE DEMAND FOR CARE IN A FREE-STANDING EMERGENCY CENTER

Free-standing emergency centers (FECs) represent a new approach to the delivery of health care which are competing for patients with more conventional forms of ambulatory care in many parts of the U.S. Currently, little is known about these centers and their patient populations. The purpose of this study, therefore, was to describe the patients who visited two commonly-owned FECs, and determine the reasons for their visits. An economic model of the demand for FEC care was developed to test its ability to predict the economic and sociodemographic factors of use. Demand analysis of other forms of ambulatory services, such as a regular source of care (RSOC), was also conducted to examine the issues of substitution and complementarity.^ A systematic random sample was chosen from all private patients who used the clinics between July 1 and December 31, 1981. Data were obtained by means of a telephone interview and from clinic records. Five hundred fifty-one patients participated in the study.^ The typical FEC patient was a 26 year old white male with a minimum of a high school education, and a family income exceeding $25,000 a year. He had lived in the area for at least twenty years, and was a professional or a clerical worker. The patients made an average of 1.26 visits to the FECs in 1981. The majority of the visits involved a medical complaint; injuries and preventive care were the next most common reasons for visits.^ The analytic results revealed that time played a relatively important role in the demand for FEC care. As waiting time at the patients' regular source of care increased, the demand for FEC care increased, indicating that the clinic serves as a substitute for the patients' usual means of care. Age and education were inversely related to the demand for FEC care, while those with a RSOC frequented the clinics less than those lacking such a source.^ The patients used the familiar forms of ambulatory care, such as a private physician or an emergency room in a more typical fashion. These visits were directly related to the age and education of the patients, existence of a regular source of care, and disability days, which is a measure of health status. ^

Infrastructure Development of Railway in Cambodia: A Long Term Strategy

Infrastructure development means for the making of living environment, transport and communications, disaster prevention and national land conservation, agriculture, forestry and fisheries, and energy production and supply. Transport infrastructure development in Cambodia involved with (1) road, (2) railway, (3) port, inland-water way and (4) aviation. All model of transport infrastructure have special different kinds of importance. Railway is different from other base important of railways are transport passengers and traffic freight especially transport for heavy goods in huge capacity and in long distance by safer and faster. Transport in Cambodia for traffic freight export import base from Thailand and other via Sisophon and Shihanoukvill port. Traffic is increasing rapidly during nowadays railway condition in adequate of demand required. This is why Railway is selected as the topic of this paper to prevent monopoly of road transport. This paper, does review about infrastructure development plan for Railway in Cambodia as a long term strategy by review and analysis forecast on the previous performance of Royal Railways of Cambodia (RRC) transport traffic involved with condition of infrastructure development of railway in Cambodia. And also review the plan of development RRC but just only detail a plan of rehabilitation that is immediately needed. Suggest some recommendation at the last part. As Cambodia is a member country of ASEAN and also Mekong sub-region. For make sure that transport networks work effectively with a progress of economic integration, we make clear what is important for infrastructure development of railway in Cambodia from the standpoint of the development plan of Mekong sub-region. This paper is organized by 4 sections. Section 1 review about Infrastructure Development of Railway in Cambodia (IDRC) Historical Background, Follow by Section 2 will review the Current Situation of IDRC and some analysis of transport performance from previous years, Then Section 3 review of the focusing on traffic transport of RRC in the future, Section 4 review Infrastructure Development of Railway in Cambodia Future plans in long term; at last conclusion and recommendation. In section 1 does review history background of RRC from the rail first begun. But why is needed to review? Because of history background is involved infrastructure development of RRC in present time. History background made big gaps constraint and obstacle for socioeconomic development and poverty reduction, also left Cambodia with tragedy and left developed behind. After that remain infrastructure development needs huge fund and long time for restoration, reconstruction, rehabilitation and development into new technology as most of world practice.

An empirical analysis of the money demand function in India

This paper empirically analyzes India’s money demand function during the period of 1980 to 2007 using monthly data and the period of 1976 to 2007 using annual data. Cointegration test results indicated that when money supply is represented by M1 and M2, a cointegrating vector is detected among real money balances, interest rates, and output. In contrast, it was found that when money supply is represented by M3, there is no long-run equilibrium relationship in the　money demand function. Moreover, when the money demand function was estimated using　dynamic OLS, the sign onditions of the coefficients of output and interest rates were found to be　consistent with theoretical rationale, and statistical significance was confirmed when money supply was represented by either M1 or M2. Consequently, though India’s central bank presently uses M3 as an indicator of future price movements, it is thought appropriate to focus on M1 or M2, rather than M3, in managing monetary policy.

The contribution of supply and demand shifts to earnings inequality in urban China

This paper examines the degree to which supply and demand shift across skill groups contributed to the earnings inequality increase in urban China from 1988 to 2002. Product demand shift contributed to an equalizing of earnings distribution in urban China from 1988 to 1995 by increasing the relative product for the low educated. However, it contributed to enlarging inequality from 1995 to 2002 by increasing the relative demand for the highly educated. Relative demand was continuously higher for workers in the coastal region and contributed to a raising of interregional inequality. Supply shift contributed essentially nothing or contributed only slightly to a reduction in inequality. Remaining factors, the largest disequalizer, may contain skill-biased technological and institutional changes, and unobserved supply shift effects due to increasing numbers of migrant workers.

A model of economic growth with saturating demand

This study presents a model of economic growth based on saturating demand, where the demand for a good has a certain maximum amount. In this model, the economy grows not only by the improvement in production efficiency in each sector, but also by the migration of production factors (labor in this model) from demand-saturated sectors to the non-saturated sector. It is assumed that the production of a brand-new good will begin after all the existing goods are demand-saturated. Hence, there are cycles where the production of a new good emerges followed by the demand saturation of that good. The model then predicts that should the growth rate be stable and positive in the long run, the above-mentioned cycle must become shorter over time. If the length of cycles is constant over time, the growth rate eventually approaches zero because the number of goods produced grows.