How Many Times Will the Fed Raise Interest Rates in 2016?

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1 IN PARTNERSHIP WITH How Many Times Will the Fed Raise Interest Rates in 2016? Applying Agent-Based Modeling and Game Theory for Estimating FOMC Behavior FEBRUARY

2 Global Impact Strategies deploys expertise in predictive analytics and decision science to address some of the world's most pressing challenges. We deliver forecasts with accuracy and speed, combining advances in mathematical modeling with expertise from the fields of political science and economics. We work with corporations, governments, and philanthropies in three main focus areas: Contributors Amir Bagherpour, PhD, Chief Political Scientist Shaun Donaldson, Senior Analyst Matthew Scharpnick, Creative Partner Acertas Mark Abdollahian, Ph.D., CEO Jacek Kugler, Ph.D., Senior Strategist Patrick Neal, Director of Engagements gistrat partnered with Acertas to complete this analysis. Acertas decodes complexity, using data, predictive and behavioral analytics to solve high risk, mission critical business challenges across strategy, management, finance, regulations, market risks and deal making. Conflict + Cooperation Energy + Environment Health + Society Visit us at gistrat.com to learn more.

3 2 Background 2 A Political Science Approach to a Political Problem 3 About the Forecasting Platform 3 Model Assumptions 3 Current Stakeholder Dispositions 8 Appendix

4 Overview Few decisions have as much impact on the US and global economy as the Federal Reserve s action on interest rates. gistrat, in partnership with Acertas, applied agentbased modeling and Monte Carlo analysis to estimate the number of times the Federal Open Market Committee (FOMC) will raise interest rates in In addition to capturing FOMC dispositions on interest rate hikes, gistrat and Acertas captured the effect of external pressures from the European Union, China, American consumers and U.S. exporters on Committee member decisions. Findings Agent-based modeling and Monte Carlo simulations indicate a minimum of two, likely three, interest rate hikes in Assuming interest rates as a priority for the FOMC, there is an 80% chance (32 out of 40 alternative futures) of three interest rate hikes by the Federal Reserve in 2016 when simulating only FOMC member positions and accounting for high variance in their positions (+-50% variance at 100% exogenous shock). Inputting the scenario where the FOMC prioritizes the issue of interest rates amongst other competing issues, the likelihood of 0, 1, 2, 3, and 4 interest rate hikes respectively are 3.9%, 17%, 27%, 39%, and 11%. Despite significant external pressure on the FOMC to halt interest rate hikes in 2016, simulations on FOMC voting indicate the Committee will likely continue to increase interest rates. Monte Carlo simulations and robustness testing of FOMC voting indicate that median and mode dispositions converge to an estimated three rate hikes in 2016 even when assuming China, EU, U.S. exporters and consumers will oppose such a hike. 1

5 Background The primary goal of the FOMC (Federal Open Market Committee) is to manage economic growth, unemployment and inflation through the appropriate monetary policy. FOMC decisions on monetary policy are supposed to be driven by market fundamentals derived from economic data. Although FOMC members theoretically make decisions in the interest of the public good, independent of political or private interests, members are often influenced by external actors. While the Federal Reserve is supposed to be an independent decision maker when it comes to monetary policy, it does not operate in a vacuum and is responsive to investor and consumer signals that could shift markets in any particular direction. Emerging from the financial meltdown of 2008, the FOMC has artificially kept interest rates to record lows of nearly 0%. In December 2015, there was a 25 basis point increase, the first rate increase in nearly a decade. The FOMC has been responsive to signals from governments and the private sector regarding the sensitivity of the world economy. The FOMC can continue to be responsive to the rhetoric of some overly sensitive governments and financial markets or return to more fundamental economic principles that would justify raising interest rates. A Political Science Approach to a Political Problem The decisions by the United States Federal Reserve over the past ten years have been divergent from most economist and financial analyst projections, partially due to the fact that FOMC behavior is not solely determined by macroeconomic fundamentals but also by political factors. Pressures shaping FOMC decisions include Congress, leaders in Europe and Asia, and the public. It is necessary to understand the political dimension of FOMC decision making even when the issues are perceived as primarily economic. Political outcomes are not determined by market forces but by competing interests that rarely produce the most efficient or effective outcomes. In an attempt to understand the political dimension of the FOMC s decision calculus, we applied an agent-based model that simulates how stakeholder and group dispositions will evolve regarding prospects of interest rate hikes in In addition to capturing FOMC dispositions on interest rate hikes, the model captures the effects of external pressure from the European Union, China, American consumers and U.S. exporters on Committee member decisions. We applied a political science lens to predict the number of interest rate hikes in 2016 because FOMC behavior is shaped by political forces rather than economic forces alone. 2

6 About the Forecasting Platform This forecast is conducted using a validated agent-based game theory model called Senturion. It incorporates computational analytics applying proven theories of behavior from the fields of psychology, political science and microeconomics to anticipate political outcomes. The U.S. State Department selected Senturion in 2014 as the most accurate model for predicting conflict and crisis outcomes at an estimated 90% accuracy level across 200+ cases. The model first generates a picture of the current political landscape on a given issue (eg. pro/anti, liberal/conservative) and then animates the picture into a dynamic simulation of how political interests will likely evolve. This approach anticipates political outcomes, details how individuals and groups evolve and adapt, sheds light on complex political interrelationships, and allows for policy design and development across multiple scenarios. In addition to agentbased modeling, the model allows for probabilistic modeling using robustness testing and Monte Carlo simulations to account for error and uncertainty. Model Assumptions The model assumes that each stakeholder or group is seeking to maximize their position relative to the influence and importance they place on the issue. The model also assumes each stakeholder is self-interested with an existing ideal preference regarding the issues (single peaked preference). Current Stakeholder Dispositions gistrat and Acertas incorporated subject matter expertise from scholars, economists, financial analysts, and journalists reporting on the issue. Importantly, our predictive analytics included estimated positions of all 17 FOMC members based on published statements. By capturing these inputs, we measured the relative power and positions of various groups and individuals, and the importance they placed on the issues. There have been over 450 projects for the U.S. Department of Defense and Intelligence Community with an 85% accuracy rate and over 200 projects at the State Department with over a 90% historic level of accuracy. The model is verified, vetted and accredited (VV&A) by multiple U.S. agencies. 3

7 Baseline Projections Indicate FOMC Will Issue Three Interest Rate Hikes in 2016 Outcome: Despite significant external pressure to halt the Federal Reserve s course on interest rate hikes in 2016, baseline simulations on FOMC voting indicates the Committee will continue with hikes. Baseline simulations indicate the majority of FOMC members will favor three interest rate hikes in Pressure to Avoid a Rate Hike China has experienced an economic slowdown partially due to admissions of false economic reporting. It will actively oppose the FOMC position on raising interest rates based on fears that any potential slowdown in the United States might negatively affect China s economy. The EU holds a similar position to China. As it has not yet recovered from the deep recession, the EU perceives an interest rate hike as too risky given current sensitive economic and political conditions. President Obama also would likely not support interest rate hikes given the risk of an economic slowdown potentially diminishing the chances of a Democrat winning the Presidency in American consumers will not seek higher interest rates either given the adverse effect it could have on their debt and financing prospects. U.S. exporters will almost certainly oppose an interest rate hike, as it would strengthen the dollar, resulting in a decrease in American exports. 4

8 Robustness Testing: Under External Political and Market Pressure FOMC Still Approves Three Interest Rate Hikes Median Position When Only FOMC Tested Median Accounted for All Stakeholders (EU, China, U.S. Consumers and U.S. Exporters) Uniform Distribution: 100% shock, +-50% variance on position and influence across 40 alternative futures Results: 32 out of 40 runs consistently at median 80% of the final positions are at the median Uniform Distribution: 100% shock, +-40% variance across 40 alternative futures Results: 14 out of 40 runs (32%) at two hikes; 10 out of 40 (25%) at three hikes; 5 out of 40 (15%) at one hike; 7 out of 40 (18%) at zero consistently at median approximately 13 at 2 (32% of the final median positions) at 0, 1, 2, and 3 rate increases respectively 5

9 Outcome: When simulating only FOMC members and accounting for high variance in their positions (+-50% variance at 100% shock), 80% of the time (32/40 futures) the final median position occurs at three interest rate hikes. When taking into account all actors, median positions vary from zero to three interest rate hikes. However, the median fluctuates because it accounts for external actor positions outside of the FOMC. Although we sought to account for volatility, we wanted to capture variance in external positions only to the extent of understanding their effect on FOMC members. This led us to focus only on the median and mode positions of FOMC members, while accounting for variance of the external actors to the extent to which they can change Committee member positions. Median and Mode of FOMC Members Extended Monte Carlo Simulations Description: Uniform Distribution, 100% shock, +-40 variance on position and influence, across 40 alternative futures Fed Member No Rates 1 Increase 2 Increase 3 Increase 4 Increase Mode Number of Increases Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Fed Net Total

10 Total Monte Carlo Analysis: 40 Alternative Futures for 17 Members of Fed (Uniform Distribution, +-40% shock range, +100% shock probability) Outcome: Monte Carlo simulations for FOMC voting indicates that the median and mode converge to an estimated three rate hikes in 2016 even when assuming that China, EU, U.S. exporters and consumers will be opposed to such a hike. We predict that at least seven of the 15 FOMC members will support three interest rate hikes in

11 Appendix Baseline: Fed Places Issue of Interest Rate Hikes as the Most Significant Priority Monte Carlo Simulations on FOMC Interest Rate Hikes Description: 40 Alternative Futures, Uniform Distribution, + 20% error and exogenous shock, 90% shock probability 8

12 Fed Places Issue of Interest Rate Hikes as One of the Most Significant Issues Along with Competing Priorities Monte Carlo Simulations on FOMC Interest Rate Hikes Description: 40 Alternative Futures, Uniform Distribution, + 20% error and exogenous shock, 90% shock probability 9

13 Fed Places Issue of Interest Rate Hikes as Important With Other Issues That Are More Important Monte Carlo Simulations on FOMC Interest Rate Hikes Description: 40 Alternative Futures, Uniform Distribution, + 20% error and exogenous shock, 90% shock probability 10

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