Balance Sheet Effects in a Financialized Environment: A Stock-Flow Consistent Framework for Mexico

ABSTRACT

Exchange rate volatility, growing foreign corporate debt, and decreasing private investment ratio are among the consequences of financialization experienced by developing countries such as Mexico. The present work analyses the combined effect of these three factors using a Stock Flow Consistent (SFC) model. It analytically explores the balance sheet effect in the non-financial corporate sector; higher foreign debt would affect private investment after episodes of real currency depreciation. To explore such mechanisms, we simulate the commodity price cycle of the early 2000s alongside the shifts in the stance of the FED in the aftermath of the Global Financial Crisis. The scenario analysis points to a hysteresis of the Real Exchange Rate (RER) and an increase in foreign debt level.

KEYWORDS:

• International finance forecasting and simulation: models and applications
• foreign exchange
• macro-based behavioural economics
• financialization

JEL CODES:

• F37
• F31
• E7

Acknowledgments

We are grateful to Juan Carlos Moreno Brid, Esteban Perez Caldentey, Michalis Nikiforos and two anonymous referees for their valuable comments on the first draft of this paper. Of course, any remaining error should be attributed to ourselves.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 According to Epstein (2005), financialization refers to the growing importance of financial interests, financial markets and financial agents and institutions in the functioning of national and international economies.

2 Own calculation with data from the Over the Counter Triennial Survey conducted by the Bank of International Settlements. Volume refers to all types of contracts traded over the counter with Mexican Peso as an underline asset.

3 The model has been built using the package ‘sfcr’ provided by Macalos (2021). The code is available upon request. The additional equations used to build the model can be found in the Appendix Three

4 Given that these securities are subject to prices changes, the role of the nominal and real yields should be separated; in our model, as reported in the Appendix Three, the latter enters in households' portfolio equations, since an increase (decrease) in their prices causes a portfolio adjustment towards (against) these assets in accordance with (Godley and Lavoie 2012, p. 132).

5 Notice that equation 5(5) ${xr}^{MX}=\frac{B_{b{US}_d}^{MX}}{B_{b{US}_s}^{MX}}$(5) implies an upward (downward) movement for appreciation (depreciation).

6 The model tries to incorporate the argument of Richard Koo (2003, 2013) from a Minskian standpoint. As soon as the price of exports falls the stock of CLN falls too, whereby the endogenous accumulation of debt (to finance investment in the upward phase of the cycle) and firms' microeconomic decisions (to revise upward their stock of capital) lead together to more fragile balance sheets which eventually feed back negatively on profits and investment.

7 The reader should remind that calibration does not intend to completely match the characteristics of either of these two countries but rather a stylized interpretation of both economies. Scenario analysis needs not to be interpreted as a macro-econometric exercise to forecast trends in variables. Instead, the study examines the impact of the shocks compared with the baseline scenario and evaluates how variables diverge from their baselines.

8 These propensities to consume are actually the ones for the whole economy, all institutional sectors considered. However, it makes sense to use them as in our model households in both economies are the only agents who consume, as both banks' and distributed firms' profits goes to them (while undistributed ones go to capital accumulation).

9 In order to calculate a proxy for the percentage change in the autonomous demand for export, we looked at data for the volume of exports of crude oil, available in the Central Bank's database. We consider the variation in the autonomous demand as a long-run change. We use the 5-year moving average of the series as a proxy for this value. We then calculate the percentage difference in December 2015 from one year later, which results in 9 per cent change in the long run (autonomous) demand for export and translates into a change from −1.18 to −1.08 in the parameter of ${\chi }_0^{LA}$.