Evaluating the performance of merger simulation using different demand systems

Competition and Market Regulation master project by Leandro Benítez and Ádám Torda ’19

Photo credit: Diego3336 on Flickr

Evaluating the performance of merger simulation using different demand systems: Evidence from the Argentinian beer market

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects. The project is a required component of all Master’s programs at the Barcelona GSE.

Abstract

This research arises in a context of strong debate on the effectiveness of merger control and how competition authorities assess the potential anticompetitive effects of mergers. In order to contribute to the discussion, we apply merger simulation –the most sophisticated and often used tool to assess unilateral effects– to predict the post-merger prices of the AB InBev / SAB-Miller merger in Argentina.

The basic idea of merger simulation is to simulate post-merger equilibrium from estimated structural parameters of the demand and supply equations. Assuming that firms compete a la Bertrand, we use different discrete choice demand systems –Logit, Nested Logit and Random Coefficients Logit models– in order to test how sensible the predictions are to changes in demand specification. Then, to get a measure of the precision of the method we compare these predictions with actual post-merger prices.

Finally, to conclude, we point out the importance of post-merger evaluation of merger simulation methods applied in complex cases, as well as the advantages and limitations of using these type of demand models.

Conclusion

Merger simulations yield mixed conclusions on the use of different demand models. The Logit model is ex-ante considered inappropriate because of its restrictive pattern of substitution, however it performed better than expected. Its predictions on average were close to the predictions of the Random Coefficients Logit model, which should yield the most realistic and precise estimates. Conversely, the Nested Logit model largely overestimated the post-merger prices. However, the poor performance is mainly motivated by the nests configuration: the swap of brands generates almost two close to monopoly positions in the standard and low-end segment for AB InBev and CCU, respectively. This issue, added to the high correlation of preferences for products in the same nest, generates enhanced price effects.

table_1_estimation_results

Regarding the substitution patterns, the Logit, Nested Logit and Random Coefficients Logit models yielded different results. The own-price elasticities are similar for the Logit and Nested Logit model, however for the Random Coefficients Logit model they are more almost tripled. This is likely driven by the estimated larger price coefficient as well as the standard deviations of the product characteristics. As expected, by construction the Random Coefficients Logit model yielded the most realistic cross-price elasticities.

table_2_elasticities

Our question on how does the different discrete choice demand models affects merger simulation –and, by extension, their policy implications– is hard to be answered. For the AB InBev / SAB-Miller merger the Logit and Random Coefficients Logit model predict almost zero changes in prices. Conversely, according to the Nested Logit, both scenarios were equally harmful to consumers in terms of their unilateral effects. However, as mentioned above, given the particular post-merger nests configuration, evaluating this model solely by the precision of its predictions might be misleading. We cannot discard to have better predictions under different conditions.

table_3_evaluation

As a concluding remark, we must acknowledge the virtues and limitations of merger simulation. Merger simulation is a useful tool for competition policy as it gives us the possibility to analyze different types of hypothetical scenarios –like approving the merger, or imposing conditions or directly blocking the operation–. However, we must take into account that it is still a static analysis framework. By focusing only on the current pre-merger market information, merger simulation does not consider dynamic factors such as product repositioning, entry and exit, or other external shocks.

Authors: Leandro Benítez and Ádám Torda

About the Barcelona GSE Master’s Program in Competition and Market Regulation

Re-examining the Global Liquidity-Asset Prices Linkage: Case of G7

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2016. The project is a required component of every master program.


Authors:
Ryan Jacildo and Ekaterina Rezepina

Master’s Program:

Macroeconomic Policy and Financial Markets

Paper Abstract:

Research concerning the linkage between global liquidity and domestic economic affairs is hardly new. Interestingly, however, it never gets old mainly because of its policy significance. The welfare impact of shocks to capital flows (may it be short or long-term) is by and large the bottom line of all the discussions. Inquiries about other pertinent issues such as global financial imbalance and asset price bubbles, international financial stability and global financial safety nets, and economic early warning systems are in one way or the other broadly tied with global liquidity. Indeed, the impact of shocks to global liquidity can be systemically disruptive. And because international financial landscape constantly changes (i.e. degree of linkages estimated in one period may not hold in the subsequent periods), regular spot checks are important. The aftershocks of the global financial crisis (GFC) in 2007/2008, for instance, re-emphasize the significance of understanding the consequences of fluxes in capital movement and the extent of these consequences in various settings and time periods.

Motivation:

The main motivation behind this study is to contribute to empirical literature on cross-border liquidity spillover effects on asset prices in light of broadening global economic integration. We decided to focus on the case of the Group of 7 (G7) economies (e.g. Canada, France, Germany, Italy, Japan, United Kingdom, and United States) and follow closely the earlier work of Darius and Radde (2010) – henceforth D&R. For the same set of economies, D&R looked at the relationship of global liquidity and asset prices before and after the “Great Moderation” period. In an attempt to provide an account of what happened after 2007, this study examines the behavior of the same variables until end of 2015 and checks whether there are significant changes to the magnitude of the pass though effects of global liquidity, particularly on the equity and property prices in recent years.

Conclusions:

In light of the developments in the past decade that led central banks to flood the international financial system with liquidity, we deem it relevant to empirically re-examine the linkage between global liquidity and asset prices in large economies. To do the econometric analysis, we used available data from 1984q1 to 2015q4 and employed a VAR model following the specification suggested by D&R.

In the global analysis, we found that global liquidity has a positive significant impact on commodity prices using the sample from 1984q1 and 2015q4 but insignificant impact on equity prices. However, in our subsample analysis using the data from 1984q1 to 2007q4, our results showed that the impulse responses of both the CRB and the MSCI were positively significant and persistent while the impulse response function of house prices remained insignificant. Interestingly, D&R, which also used 1984q1 to 2007q4 as its Great Moderation subsample, found that the responses of commodity and equity prices to a liquidity shock were insignificant. In terms of the house prices, the results we obtained differed from those of D&R for periods from 1984q1 to 2007q4 in a sense that we found significantly negatively response to global liquidity albeit with a substantial lag of 16 quarters.

jacildo-rezpina1

In our spillover analysis, we extended the model of D&R by adding the local stock prices to the model. For each economy, we ran the regression using data from 1984q1 to 2015q4 as well as from 1984q1 to 2007q4 (to serve as our pre-GFC subsample). The results of this exercise convey that the positive effect of a global liquidity shock on house prices in Japan obtained using data from 1984q1 to 2015q period disappears when only pre-GFC period is considered. In the full sample analysis both global and domestic liquidity did not affect stock prices in Japan, whereas the effect of global liquidity turned out to be positive for the pre-GFC period.

Notwithstanding the sample used (may it be full or pre-GFC), the effect of global liquidity on house prices in France stays significant and negative, while the negative impact of global liquidity on stock prices obtained using full sample disappears in pre-GFC subsample. In the case of the latter, the stock prices turned out to be significantly positively affected by local liquidity, while the inclusion of post crisis years made this response negatively significant with a substantial lag.

Lastly, the result of the pre-GFC subsample analysis involving the UK reveals that the effect of local liquidity shock on stock prices is not significant as opposed to full sample estimation when the effect was positive. Moreover, the variance decomposition dictates that global GDP growth rate explains the largest proportion of the volatility of stock prices in the UK.

Moving forward, one way to get a better understanding of the results would be to properly assess the country-level intertemporal idiosyncratic factors just like in the global analysis. Certainly, the nature and timing of these structural shifts can vary from one country to another. We likewise suggest trying different proxies for the global liquidity or run the model for the monthly data without house prices that are available only quarterly and the monthly proxy for GDP. Using monthly data would allow a closer analysis of dynamics in the post-GFC period. It would also be interesting to extend the scope of this exercise to emerging economies.

Riding the barrel: How commodity exporters can maneuver through price rapids

Master project by Martin Aragoneses, Mario Giarda, and Nikolas Schöll. Barcelona GSE Master’s in Economics

Editor’s note: This post is part of a series showcasing Barcelona GSE master projects by students in the Class of 2015. The project is a required component of every master program.


Authors: 
Martin Aragoneses, Mario Giarda, and Nikolas Schöll

Master’s Program:
Economics

Paper Abstract:

We develop a multi-sector small open economy DSGE model with government and exogenous sources of income, in particular where the country is a commodity producer such that income from commodity exports provides a large proportion of government revenue, making international uncertainty about the future commodity price matter. The objectives of this paper are to study the differences between level shocks and uncertainty shocks to commodity prices in terms of how they affect the economy, and to analyze the convenience of different fiscal rules when we allow the income processes to have moving uncertainty.

In an application, we estimate the parameters of a stochastic volatility model for Angola and Chile and we feed them to the model to see different economic responses to uncertainty shocks. Then, we investigate whether the fiscal rule should depend on the type of income process in general. In our evaluation, we focus on the short term implications of the rule in reducing volatility, wondering if it is better to spend the resources in the present than have an insurance against the cycles? Finally, we discuss some policy implications regarding the implementation of those rules. Can the rule be tractable by the agents on the model? Are the best rules sufficiently simple to be followed by the public and finally credible as an anchor of the expectation

Presentation Slides: