The health system in Colombia faces several important challenges. Some of these challenges include financial solvency given the increasing costs of providing health services; offering quality care in the face of growing demand of low and high complexity services; and market asymmetries due to market organization and the incentives to the agents that participate in it.The area of economic models at Quantil has a long trajectory in the study of the Colombian health system using tools of health economics.

Among the research we have done we may list: (i) the estimation of optimal capital of health insurers using information from the Health Ministry,based on ruin theory; (ii) the estimation of the impact of changes in the Compulsory Health Plan on social welfare; (iii) a comparison of alternative ways of adjusting risk ex-ante in health, with respect to the current policy of the Ministry that uses Payment Unit for Capitation (UPC); (iv) the evaluation of alternative ways of adjusting risk ex-post with respect to the current mechanism of the Ministry, High Cost Account (CAC by its Spanish acronym); (v) the evaluation of the impact of forms of contract between insurers and service providers over health care results for the users of the contribution-based system in Colombia, using the data bases of the Ministry and the theory of contracts under asymmetric information; (vi) the prediction of health care results for the patients in an intensive care unit using the information in a high-level hospital in Cali and applying empirical tools of machine learning; and (vii) the evaluation of a program to prevent hospitalizations in the Colombian health care system, finding potential savings in costs for different combinations of efficacy of the program and costs of intervention per patient.

Most electricity markets in the world function under mechanisms of auctions market for multi-units. These mechanisms are designed with the goal of fostering enough competition between electricity generators in order to maximize social efficiency. However, the economics literature has shown in the last decade that the existing market designs do not always achieve this goal. Particularly, technical inflexibilities, the variability of weather conditions, barriers to entry, and the exercising of market power by the agents are the main characteristics causing inefficient dispatch of electricity from an economic standpoint.

Recent economics studies on these markets have implemented different strategies for the estimation of econometric models that allow to infer fundamental non-observed characteristics of the companies and the market in general for different mechanisms. The methodology is based on the estimation of auctions models for electricity markets. These studies have the goal of measuring the negative effect of the abovementioned aspects over market performance and to produce proposals for the design of alternative mechanisms that minimize the losses of efficiency that they cause.

Quantil has done these studies using economic models of last generation, with a commitment to objectivity and rigor, as well as to fulfilling the customers’ needs.

The estimated models allow for:

  • Measuring the level of market power exerted by the companies in the wholesale market.
  • Measuring and evaluating the economic efficiency of several variations of the market mechanism that allocate electricity production by the market operator towards the electricity generators.
  • Calculating the value of contracts of contracted energy, bilaterally and with the market operator.
  • Measuring the financial risk exposure for the market operator under different regulatory schemes.
  • Evaluating the benefits associated with the introduction of unconventional technologies for electricity generation.

The next chart shows the evolution in the 2001-2009 period of the estimated price-cost margin for hydroelectric plants in the Colombian electricity market, discriminating between the component associated with market power (static markup) and that associated with the cost of opportunity of water (dynamic markup).

In 2013, the telecommunications sector in Colombia completed more than 7 million subscriptions to broadband Internet and mobile phone coverage of almost 100% (MINTIC). This is why regulatory policies directed to this sector are important for the consumers, considering that either it is possible to reach the goals set by the regulations or to have adverse effects. Therefore, it is crucial to evaluate the social impact of these policies.

Models based on economic theory and quantitative methods allow to model the main relationships existing in this sector: a variety of plans, heterogeneous customers, non-linear pricing systems, time gap between the acquisition of a phone plan and its consumption, minimum contract stay clauses, and network effects. These models, together with the understanding of the market and econometrics projections, allow to explain the impact of competition on consumers, on providers’ benefits, and on the government.

Quantil has undertaken these studies using economic models of last generation, with a commitment to objectivity and rigor, as well as to fulfilling the customers’ needs.

In the telecommunications sector, we did a research project to measure the impact of the elimination of minimum contract stay clauses on the wellbeing of consumers and providers. Until July of 2014, cellphone service providers could sell cellphones and voice and data plans as packages, assuring a minimum stay of the users in their network. At that time, the Commission for the Regulation of Communications (CRC) issued Resolution 4444 forbidding minimum stay clauses in cellphone contracts. Using the theory of industrial organization and models of discrete choice with random coefficients, we found that the resolution has increased consumer wellbeing in two ways: by decreasing the margins over the price of cellphones sold by mobile service providers (see graph below) and by increasing the variety of available cellphones, thanks to the entry of competitors in the business of selling mobile phones. Aggregated, the benefits for consumers are close to COP$7 billion a month.

Quantil offers an objective analysis of scenarios that can compromise competition in a market. Supported by solid theoretical bases and with the use of empirical data, it is possible to determine what effect may have the merging of several companies or agreements compromising free competition.

Most models can be executed with relatively few information. For example, calibrating a PCAID model only requires inputting the participation in the market of the different companies or brands in it, the elasticity of demand at the price of all the business, and of some brand. With this information it is possible to determine the change in prices caused by a merger. However, more available information (with better quality) makes it possible to develop more models and to obtain more accurate results.

Other type of models are based on the literature of the New Empiric Industrial Organization (NEIO). This methodology consists in inferring, from observed data on prices and quantities, unobserved attributes of supply and demand according to a given structure of competition. Then, the estimated attributes of the model are used to contrast the validity of the behavior hypotheses assumed. Particularly, the estimated model allows to measure the degree of market power exerted by companies, as well as determining if the companies behave according to a competition benchmark or not.

Quantil offers the following analyses:

  • Price correlation: It allows to determine the closeness of the prices of two products during a period of time. This analysis is performed over stationary series to avoid inconsequential relationships.
  • Price elasticity of demand: An econometric analysis that allows to determine the percentage of change in the demand of a product (or group of products) due to a change in its price. The more elastic the demand, the less likely to find and increase in price.
  • Cross elasticity: With an econometric analysis it is possible to determine the percentage of change in the demand of a brand due to a change in the price of another product. With this information it is possible to determine if two products are close substitutes or not. When analyzing the merger of two companies, it is very important to consider if their products are close substitutes or not.
  • Measurement of market power, aggregated or by company (according to level of detail of the data used).
  • Contrasting hypotheses about different competition levels among the companies.
  • Mergers simulation. The market is modeled at its pre-merger state. Then, it is supposed that some companies merge and the effect of the merger over prices and the companies’ participation is calculated.
  • Price-Concentration relationship: An econometric model allows to determine the relationship between concentration indices and the prices in a market. This information allows to determine the increase in prices that can be caused by a merger.
  • Damage assessment: The use of econometric techniques makes it possible to determine the impact of anti-competitive behaviors.