In this article, we describe twopm, a command for fitting two-part models for mixed discrete-continuous outcomes. In the two-part model, a binary choice model is fit for the probability of observing a positive-versus-zero outcome. Then, conditional on a positive outcome, an appropriate regression model is fit for the positive outcome. The twopm command allows the user to leverage the capabilities of predict and margins to calculate predictions and marginal effects and their standard errors from the combined first-and second-part models.

This article describes sfcross and sfpanel, two new Stata commands for the estimation of cross-sectional and panel-data stochastic frontier models. sfcross extends the capabilities of the frontier command by including addi

Aging is a strong risk factor for many chronic diseases. However, the impact of an aging population on the prevalence of chronic diseases and related healthcare costs are not known. We used a prevalence‐based approach that combines accurate clinical and drug prescription data from Health Search CSD‐LPD. This is a longitudinal observational data set containing computer‐based patient records collected by Italian general practitioners (GP) and up‐to‐date healthcare expenditures data from the SiSSI Project. The analysis is based on data collected by 900 GP on an unbalanced sample of more than 1 million patients aged 35+, observed in different time periods between 2005 and 2014. In 2014, 86% of the Italian adults older than 65 had at least one chronic condition, and 56.7% had two or more. Prevalence of multiple chronic diseases and healthcare utilization increased among older and younger adults between 2004 and 2014. Indeed, in the last 10 years, average number of prescriptions increased by approximately 26%, while laboratory and diagnostic tests by 27%. The average number of DDD prescribed increased with age in all the observed years (from 114 in 2005 to 119.9 in 2014 for the 35–50 age group and from 774.9 to 1,178.1 for the 81+ patients). The alarming rising trends in the prevalence of chronic disease and associated healthcare costs in Italy, as well as in many other developed countries, call for an urgent implementation of interventions that prevent or slow the accumulation of metabolic and molecular damage associated with multiple chronic disease.

xsmle is a new command for spatial analysis using Stata. We consider the quasi-maximum likelihood estimation of a wide set of both fixed-and randomeffects spatial models for balanced panel data. Of special note is that xsmle allows to handle unbalanced panels thanks to its full compatibility with the mi suite of commands, to use spatial weight matrices in the form of both Stata matrices and spmat objects, to compute direct, indirect and total marginal effects and related standard errors for linear (in variables) specifications, and to exploit a wide range of postestimation features, extending to the panel data case the predictors proposed by Kelejian and Prucha (2007). Moreover, it also allows the use of margins to compute total marginal effects in presence of nonlinear specifications obtained using factor variables. This paper describes the command and all its functionalities using both simulated and real data.

xsmle is a new command for spatial analysis using Stata. We consider the quasi-maximum likelihood estimation of a wide set of both fixed-and randomeffects spatial models for balanced panel data. Of special note is that xsmle allows to handle unbalanced panels thanks to its full compatibility with the mi suite of commands, to use spatial weight matrices in the form of both Stata matrices and spmat objects, to compute direct, indirect and total marginal effects and related standard errors for linear (in variables) specifications, and to exploit a wide range of postestimation features, extending to the panel data case the predictors proposed by Kelejian and Prucha (2007). Moreover, it also allows the use of margins to compute total marginal effects in presence of nonlinear specifications obtained using factor variables. This paper describes the command and all its functionalities using both simulated and real data.

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a b s t r a c tUsing data from 1176 Italian municipalities in 2005, we identify factors associated with the development of e-government services supplied by local public administrations (PAs). We show that the combination of internal competencies and context-specific factors is different when explaining decisions to start e-government activities vs. the intensity of such activities. Municipalities involved in e-government are larger, carry out more in-house ICT activities and are more likely to have intranet infrastructures than PAs that do not offer front-office digitized services. They are also generally located in regions having relatively large shares of firms using or producing ICTs, where many other municipalities offer digitized services, and where population density is relatively low. The range and quality of e-government services supplied by local PAs tend to increase with their stock of ICT competencies, their efforts to train workers, and with their ability to organise efficient interfaces with end-users. Moreover, there is a correlation between the range and quality of e-government services offered and the broadband infrastructure development in the area where local PAs are located.