Estimating Size of Drug Users in Macau: an Open Population Capture-Recapture Model with Data Augmentation Using Public Registration Data

Successful drug intervention policies rely on timely assessment of size of drug users and close monitoring of trend regarding drug abuse. Taking advantage of data collected by the Central Registration System for Drug Abusers of Macau (CRSDAM), this study applied open population capture-recapture models with data augmentation techniques to estimate the size of drug users and to identify influential factors on capture and survival probabilities from 2009 to 2014. In particular, the data augmentation technique was used to address missing data issues. The estimated size of drug users has been slowly declining from 2442 (95% Bayesian credible interval [BCI] 2042–2914) in 2009 to 807 (95% BCI 654–1000) in 2014 with a small fluctuation of 2251 (95% BIC 1950–2599) in 2011, and the estimated cumulative size of drug users is 6199 (95% BCI 5651–6873), which is correspondent to a prevalence rate of 1.20% of the current population aged 15 to 54. Although the estimated sizes of total, narcotic, and other drug users were declining, the size of stimulant users might be increasing. People who used narcotics as their first drug and who were reported by governmental agencies were more likely to stay in the registration system, while those who used needle injection were less likely to stay. Governmental agencies, higher education, and using needle injection were negatively associated with the probability of capture over time, while using narcotics as the first drug was positively associated with it.     

Multilevel public funding for small business innovation: a review of US state SBIR match programs

US State governments invest in early-stage innovative activity as an economic development strategy. Nevertheless, attention directed at the public sector’s role in this capacity has been placed on federal policy actions overlooking the growing role of states. The primary aims of this paper are two-fold: (1) to articulate the motivations for multilevel public support for small business innovative activity, placing emphasis on state level incentives directed towards entrepreneurial activity; and (2) to empirically evaluate the State Match Phase I (SMP-I) program. The SMP-I program is a diffuse state level policy designed to complement the federal Small Business Innovation Research (SBIR) program by offering noncompetitive matching funds to the state’s successful SBIR Phase I recipients. This offers an opportunity to examine the marginal impact of public R&D given the state intervention. This paper employs a state and year fixed effects model and considers two outcome variables—SBIR Phase II success rates and SBIR Phase I application activity. To account for industrial heterogeneity, the data are stratified by the federal mission agencies. Results from the empirical analysis indicate that the state match increases the Phase II success rates for firms participating in the National Science Foundation SBIR program.