The instrumental variables structural vector autoregression (IVSVAR) method is an alternative to the traditional short-run SVAR that allows us to identify and track the impact of one or more shocks on a system of autoregressive equations. Linear projection impulse–response functions (LPIRF) are an alternative to the traditional IRF that directly estimates the impact of a shock, rather than calculating the impact from parameters estimated by a VAR or an SVAR. The Stata commands ivsvar and lpirf implement these methods and are among the newest tools for time series.

Meta-analysis is a statistical technique for synthesizing the results of several studies. For example, suppose several studies have reported different estimates of the efficacy of a tuberculosis vaccine; meta-analysis allows us to synthesize the results of all the studies in order to obtain a single value of the vaccine's efficacy. Additionally, if the effect sizes are grouped by level, we can take into account the dependence between grouped observations to build more accurate inferences. I will present how to perform a proportion meta-analysis and a multilevel meta-analysis in Stata 18.

We studied the effects of the transition from a retrospective to a prospective payment scheme for medicines to health insurers using data on medicines sold in Colombia between 2011 and 2018. We compared over time the results of included medicines with those that were not and used difference-in-differences models with stepped treatment to estimate the effects on the mean and distribution of prices, quantities, and expenditures on medicines. The results indicate that the change to a prospective payment scheme increases the quantities of low-selling medicines and decreases the prices of included medicines. The effect on the distribution of total expenditure on medicines is mixed: expenditures increase in the lowest percentiles but decrease in the highest percentiles. Significant growth in the prices and quantities of non-UPC medicines suggests strategic responses by insurers.

Considering the recent spread and growing interest in epidemiology, during this presentation, I will review some basic concepts that constitute the foundations of this scientific discipline, including its object of study. I will briefly describe the arithmetic concepts that form the basis of the analysis; I will describe the concept of risk, its measurement, and two interpretations of its estimation; and finally, I will review examples of estimates of the most commonly used frequency measures, of the simple estimation of relative risk from them, and of the attributable fraction based on the latter, briefly describing its interpretation.

In recent years, Latin American government entities have strengthened their information management processes in areas such as security, interoperability, transparency, and disclosure, seeking to formalize and standardize minimum quality criteria for data processing and to facilitate the public use of data through open data initiatives and periodic reports. In this presentation, I will address the importance of having an adequate data management process as a preliminary step for any type of analysis, the particular challenges that these entities face in managing their data, and the tools that Stata has to support analysts in this task.

Data collection through large-scale censuses or surveys provides relevant historical information for data analysis at the government level or by private organizations that can be used to make relevant decisions at the economic or public policy level. In this talk, I will present an example of the application of panel-data analysis with information from the Chilean Social Protection Survey and the different analytical possibilities that Stata offers for working with this type of data.

The efficient markets hypothesis (EMH) theory has been the traditional basis for understanding the behavior of financial markets. However, in recent decades, the adaptive markets hypothesis (AMH) has emerged as an alternative that offers a more flexible and dynamic view. The AMH proposes that financial markets are neither static nor perfectly efficient but rather evolve and adapt based on the interaction between market participants, their strategies, and the economic environment. In this presentation, I will explore financial market efficiency from an EMF perspective. A recent empirical study will be discussed that illustrates how markets adapt to new environments and how this challenges some of the key assumptions of EMF. In addition, practical implications for investors, regulators, and market participants will be addressed, highlighting the opportunities and risks associated with market adaptability.