A Nail-Biter in ANALYSIS A Nail-Biter in 2016

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1 ECONOMIC & CONSUMER CREDIT ANALYTICS ANALYSIS A Nail-Biter in 2016 August 2015 A Nail-Biter in 2016 Prepared by Mark Zandi Mark.Zandi@moodys.com Chief Economist Dan White Daniel.White@moodys.com Associate Director Chris Lafakis Chris.Lafakis@moodys.com Associate Director Michael Brisson Michael.Brisson@moodys.com Assistant Director Abstract It s the economy stupid. It was the 1992 presidential election, and Clinton adviser James Carville was exhorting the campaign to focus on what mattered most to voters: their pocketbooks. The economy may not be at the top of voters minds in every election, but it is close. This is the principle underpinning the Moody s Analytics presidential election model. The model predicts whether the Democratic or Republican presidential nominee will win the popular vote in each state and the District of Columbia. In our Electoral College system, the candidate who wins the plurality of votes in enough states with a total of at least 270 electoral votes wins the election. Contact Us help@economy.com U.S./Canada EMEA (London) (Prague) Asia/Pacific All Others Web

2 ANALYSIS A Nail-Biter in 2016 BY MARK ZANDI, DAN WHITE, CHRIS LAFAKIS AND MICHAEL BRISSON the economy stupid. It was the 1992 presidential election, and Clinton adviser James Carville was exhorting the campaign to focus on what mattered most to voters: their pocketbooks. It s The economy may not be at the top of voters minds in every election, but it is close. This is the principle underpinning the Moody s Analytics presidential election model. The model predicts whether the Democratic or Republican presidential nominee will win the popular vote in each state and the District of Columbia. In our Electoral College system, the candidate who wins the plurality of votes in enough states with a total of at least 270 electoral votes wins the election. The model is constructed based on presidential election results since the 1980 Reagan-Carter contest, and captures the impact on voting decisions of the health of state economies in the lead-up to the election as well as the party affiliation and political realities in each state. The model is similar to the one we used to successfully predict President Obama s victories in 2008 and There are other election models that use economics to help explain election outcomes, but the Moody s Analytics model is the only one we are aware of that fully incorporates state-level economic activity. This is key since the election is won or lost in the state Electoral College. To cut to the chase, we predict that the Democratic nominee for president will win the election by the slimmest of margins with precisely 270 electoral votes. The Republican nominee will fall just short with 268 votes. Economics in the model The election model explains the share of the popular vote in each state that the incumbent party will win based on the strength of each state s economy and its politics. The most important economic variable in the election model is the growth in real personal income per household in the two years leading up to the election (see Table 1). This variable captures the strength of the job market in each state, including job growth, hours worked, wage growth, and the quality of the jobs being created. It also captures how well households are doing on some of their investments, as it includes dividends, interest income and rents. Since it is on a real or after-inflation basis, it also captures the impact of inflation on the purchasing power of households income. With regard to the current presidential election cycle, household incomes have been steadily improving in most of the country. Job growth has been robust, hours are back close to previous highs, and jobs across all pay scales are being created. The only missing ingredient is stronger wage growth, which is expected to pick up in coming months as the job market approaches full employment. Inflation is also low. Real household income growth thus favors the incumbent party, the Democrats. The growth in house prices in the two years preceding the election also influences voting decisions. A two-year percent change is likely measuring, at least in part, expectations regarding future house price growth, as house price expectations appear to form adaptively. That is, homeowners base their thinking about future price growth on recent price gains. House prices also matter only to voting beginning with the 2004 election, which is consistent with the timing of the formation of the house price bubble. Prior to that, house prices mostly always rose in most of the country at close to the pace of household income. The recent rebound in house prices in the wake of the housing bust again augurs well for the incumbent Democrats. House prices are expected to be rising solidly in most of the country prior to the election. The final economic variable included in the election model is the percent change in gasoline prices in the two years leading up to the election. Gas prices are a very visible price that matters significantly to the finances and perceptions of many households. Consumer confidence is closely tied to movements in gas prices, as rising prices quickly undermine confidence and falling prices lift spirits. Oil and gasoline prices have fallen sharply over the past year (almost $1 per gallon), and prospects are good that they will remain low through Election Day. The Saudis continue to increase their production despite the much lower global prices, and it looks increasingly likely that there will be a finalized deal with the Iranians over their nuclear program, which means Iran will soon be pumping more oil. Low gasoline prices also favor the incumbent Democrats. MOODY S ANALYTICS / Copyright

3 ANALYSIS A Nail-Biter in 2016 Table 1: What Explains the Share of the Vote That Goes to the Incumbent Party? Pooled Least Squares Regression 51 Cross Sections 1980 to Observations Coefficient Std Error T-statistic Constant Real income per household, 2-yr % change Real house price growth, 2-yr % change Gasoline prices, 2-yr % change Incumbent party share in previous election independent coefficient for each state, all close to 1 and highly significant Fatigue dummy Democrat dummy President s approval rating, 2-yr % change R-Squared 0.91 Durbin Watson 2.07 Source: Moody s Analytics intuition has also been borne out in other studies of voting patterns. The trajectory of the president s approval rating also makes a meaningful difference. If the sitting president s approval rating is improving in the year leading up the election, the incumbent party receives a boost in the election. In most elections, the president s rating has declined in the lead-up to the election, favoring the challenger party. It is assumed in our 2016 prediction that President Obama s approval rating will be the same on Election Day as it is today. Being a favorite son appears to matter in some elections, but not enough to enter into the model. Being a favorite son mattered most in Ronald Reagan s 1980 win in California, which is a Democratic-leaning state, and Bill Clinton s victory in 1992, when he won Republican-leaning Arkansas. The national political backdrop strongly favors the presidential bid of the Republican nominee. While real household income, house prices, and gasoline prices are included in the election model, many other variables were tested to see whether they made the model more predictive. Unemployment, stock prices, employment growth, consumer confidence, and many other variables were tested. None worked as well in explaining election outcomes. The economy s performance strongly favors the Democratic nominee for president. Politics in the model While economics matter a lot on Election Day, so too do politics. Most important, most states tend to vote consistently Democrat or Republican, regardless of whatever else is going on. Massachusetts, for example, is a dark blue state, while Wyoming is dark red. It is hard to imagine what would change voting patterns in these states. This reality is captured in the model by including the share of the vote that went to the incumbent party in the previous election as a variable. In so-called swing states, the share of the vote that goes to the incumbent party is close to 50%. In these states, economic and other factors can swing the vote to either party. The key swing states include Colorado, Florida, Ohio and Virginia. Iowa, New Hampshire, Nevada, Pennsylvania and Wisconsin have also been swing states in past elections. Another political factor that will likely play an important role in the current election is voter fatigue. Historically, the electorate tends to vote the incumbent party out of the presidency if the party has been in office for two consecutive terms. Think Bill Clinton and George W. Bush. The exception of course is George H.W. Bush, who won in 1988 despite following the two Ronald Reagan terms. The fatigue factor weighs heavily against the Democratic nominee in this election. A number of swing states would likely vote Democratic in 2016 if not for voter fatigue. This is particularly applicable given that the model also includes a variable that down-weights previous voting shares if the incumbent is a Democrat. The intuition is that Democratic voters tend to be less politically ideological than Republicans and are more likely to vote non-democratic. This Model accuracy The presidential election model has accurately predicted every presidential election since Over the nine elections since 1980, the model accurately predicted the winning party in 406 of the 459 elections in the 50 states and DC (see Table 2). Nearly all of the misses across states were for very small states, and there were no states that the model missed on a consistent basis. The model nailed the 2012 election, accurately predicting the election outcome in all of the states and hitting the Electoral College vote on the nose. The model did least well predicting the 1992 election between Bush senior and Bill Clinton. Predicting this election was significantly complicated by Ross Perot s third-party candidacy, in which he won nearly one-fifth of the popular vote and severely hurt Bush s reelection bid. The model also nearly missed the controversial 2000 race between George W. Bush and Al Gore, which was ultimately decided by the Supreme Court. Democrats win barely The next president should be a Democrat (see Map). According to the model, the MOODY S ANALYTICS / Copyright

4 ANALYSIS A Nail-Biter in 2016 Table 2: Moody s Analytics U.S. Election Model Historical test results and forecast Yr Actual election results Incumbent party s electoral votes Winning party Predicted election results Incumbent party s electoral votes Winning party Republican 82 Republican Republican 523 Republican Republican 469 Republican Democrat 191 Democrat Democrat 402 Democrat Republican 169 Republican Republican 284 Republican Democrat 173 Democrat Democrat 332 Democrat Democrat 2016 Election Will Be a Nail-Biter How states will vote, Aug 2015 forecast Source: Moody s Analytics Democrat Republican Electoral count Democrats: 270 Republicans: 268 Table 3: Expected State Vote in 2016 Election % for incumbent in 2016 presidential election Source: Moody s Analytics Solid Democrat Aug-15 Democrat should win 270 electoral votes to 268 for the Republican (see Table 3). The key swing state to push the election to the Democrats is Virginia. The Republican candidate will win Florida. The election appears to hinge critically on Ohio and Virginia. Based on research modeling election results at the county level, the vote in Ohio thus appears to depend critically on the vote in Hamilton County (Cincinnati), which is historically Republican, and Cuyahoga County (Cleveland), which is historically Democrat. The 2016 presidential election could thus come down to voter turnout in Hamilton and Cuyahoga counties not much of an endorsement for the Electoral College approach to picking presidents. Virginia is also on the fence. If President Obama s approval rating falls by any more than 2 percentage points by Election Day, Virginia will swing and the Republicans will win the presidency. These results are subject to a significant degree of uncertainty and will change as more economic data come in. The current results are based entirely on the Moody s Analytics projections for real household income growth by state and gasoline prices as of the third quarter of If our forecasts of income growth are overly optimistic, then the Democrats will not do as well as currently expected. And if gas prices, which are expected to remain low, instead rise, that too would boost Republican chances. The model results are less valid if either political party nominates a non-establishment candidate. Elections since 1980 have been between candidates who are generally thought to be largely in the mainstream of American politics. Some of the current presidential candidates are more on the fringes of the political spectrum. Of course, it is a bit (a lot) self-centered to think elections revolve simply around financial matters. Surely foreign affairs, social issues and personalities matter also. And at times they matter most of all. But in most times, and 2016 appears to be Leaning Democrat Aug-15 Solid Republican Aug-15 DC 94.7% MI 52.9% GA 44.7% HI 69.8% OR 52.7% MS 43.9% RI 66.2% WI 51.8% SC 43.7% VT 65.7% MN 51.7% AZ 43.0% NY 64.9% NM 51.6% MO 42.7% MD 63.3% PA 51.3% IN 42.3% MA 61.5% NH 50.7% AK 40.9% NJ 59.6% IA 50.6% LA 40.8% CT 59.1% VA 50.2% TX 39.9% CA 59.0% Leaning Republican TN 38.9% DE 58.2% OH 49.9% AL 38.4% IL 56.1% FL 49.8% MT 38.1% WA 55.9% CO 48.7% SD 37.1% ME 55.8% NV 47.9% KY 36.8% NC 47.0% KS 36.7% NE 36.5% ND 36.2% AR 35.0% WV 34.4% OK 31.8% ID 30.5% WY 26.9% UT 23.2% stacking up as one of those times, it is the economy stupid. MOODY S ANALYTICS / Copyright

5 AUTHOR BIO About the Authors Mark Zandi Mark M. Zandi is chief economist of Moody s Analytics, where he directs economic research. Moody s Analytics, a subsidiary of Moody s Corp., is a leading provider of economic research, data and analytical tools. Dr. Zandi is a cofounder of Economy.com, which Moody s purchased in Dr. Zandi s broad research interests encompass macroeconomics, financial markets and public policy. His recent research has focused on mortgage finance reform and the determinants of mortgage foreclosure and personal bankruptcy. He has analyzed the economic impact of various tax and government spending policies and assessed the appropriate monetary policy response to bubbles in asset markets. A trusted adviser to policymakers and an influential source of economic analysis for businesses, journalists and the public, Dr. Zandi frequently testifies before Congress on topics including the economic outlook, the nation s daunting fiscal challenges, the merits of fiscal stimulus, financial regulatory reform, and foreclosure mitigation. Dr. Zandi conducts regular briefings on the economy for corporate boards, trade associations and policymakers at all levels. He is on the board of directors of MGIC, the nation s largest private mortgage insurance company, and The Reinvestment Fund, a large CDFI that makes investments in disadvantaged neighborhoods. He is often quoted in national and global publications and interviewed by major news media outlets, and is a frequent guest on CNBC, NPR, Meet the Press, CNN, and various other national networks and news programs. Dr. Zandi is the author of Paying the Price: Ending the Great Recession and Beginning a New American Century, which provides an assessment of the monetary and fiscal policy response to the Great Recession. His other book, Financial Shock: A 360º Look at the Subprime Mortgage Implosion, and How to Avoid the Next Financial Crisis, is described by the New York Times as the clearest guide to the financial crisis. Dr. Zandi earned his BS from the Wharton School at the University of Pennsylvania and his PhD at the University of Pennsylvania. He lives with his wife and three children in the suburbs of Philadelphia. Dan White Dan White is a Senior Economist at Moody s Analytics, responsible for coordinating government consulting and regional economic research with an emphasis on fiscal policy. He regularly presents to clients and conferences, and has been featured in a number of print, radio, and televised media outlets, ranging from the Wall Street Journal to National Public Radio. He also has the pleasure of working closely with a number of governments in a consulting role. Before joining Moody s Analytics, Dan worked as a financial economist for the New Mexico State Legislative Finance Committee in Santa Fe, where he forecast revenues and analyzed a wide range of policy issues concentrated around economic development, public investment, and debt management. Dan holds an MA in economics as well as undergraduate degrees in finance and international business from New Mexico State University. Chris Lafakis Chris Lafakis is a senior economist at Moody s Analytics. His expertise is in macroeconomics, model development, model validation and energy economics. Based in West Chester PA, he also covers the California economy and contributes to the Dismal Scientist web site. Mr. Lafakis received his bachelor s degree in economics from the Georgia Institute of Technology and his master s degree in economics from the University of Alabama. Michael Brisson Michael Brisson is an economist at Moody s Analytics. He develops state and local revenue forecasts on various consulting projects and is a frequent contributor on energy-related issues. Mike holds a PhD in Applied Economics from Northeastern University, an MS in Economics from the University of Buffalo, and a BA in Political Science from the State University of New York at Oswego. MOODY S ANALYTICS / Copyright

6 About Moody s Analytics Economic & Consumer Credit Analytics Moody s Analytics helps capital markets and credit risk management professionals worldwide respond to an evolving marketplace with confidence. Through its team of economists, Moody s Analytics is a leading independent provider of data, analysis, modeling and forecasts on national and regional economies, financial markets, and credit risk. Moody s Analytics tracks and analyzes trends in consumer credit and spending, output and income, mortgage activity, population, central bank behavior, and prices. Our customized models, concise and timely reports, and one of the largest assembled financial, economic and demographic databases support firms and policymakers in strategic planning, product and sales forecasting, credit risk and sensitivity management, and investment research. Our customers include multinational corporations, governments at all levels, central banks and financial regulators, retailers, mutual funds, financial institutions, utilities, residential and commercial real estate firms, insurance companies, and professional investors. Our web periodicals and special publications cover every U.S. state and metropolitan area; countries throughout Europe, Asia and the Americas; the world s major cities; and the U.S. housing market and other industries. From our offices in the U.S., the United Kingdom, the Czech Republic and Australia, we provide up-to-the-minute reporting and analysis on the world s major economies. Moody s Analytics added Economy.com to its portfolio in Now called Economic & Consumer Credit Analytics, this arm is based in West Chester PA, a suburb of Philadelphia, with offices in London, Prague and Sydney. More information is available at , Moody s Corporation, Moody s Investors Service, Inc., Moody s Analytics, Inc. and/or their licensors and affiliates (collectively, MOODY S ). All rights reserved. ALL INFORMATION CONTAINED HEREIN IS PROTECTED BY COPYRIGHT LAW AND NONE OF SUCH INFORMATION MAY BE COPIED OR OTHERWISE REPRODUCED, REPACKAGED, FURTHER TRANSMITTED, TRANSFERRED, DISSEMINATED, REDISTRIBUTED OR RESOLD, OR STORED FOR SUBSEQUENT USE FOR ANY PURPOSE, IN WHOLE OR IN PART, IN ANY FORM OR MANNER OR BY ANY MEANS WHATSOEVER, BY ANY PERSON WITHOUT MOODY S PRIOR WRITTEN CONSENT. All information contained herein is obtained by Moody s from sources believed by it to be accurate and reliable. Because of the possibility of human and mechanical error as well as other factors, however, all information contained herein is provided AS IS without warranty of any kind. Under no circumstances shall Moody s have any liability to any person or entity for (a) any loss or damage in whole or in part caused by, resulting from, or relating to, any error (negligent or otherwise) or other circumstance or contingency within or outside the control of Moody s or any of its directors, officers, employees or agents in connection with the procurement, collection, compilation, analysis, interpretation, communication, publication or delivery of any such information, or (b) any direct, indirect, special, consequential, compensatory or incidental damages whatsoever (including without limitation, lost profits), even if Moody s is advised in advance of the possibility of such damages, resulting from the use of or inability to use, any such information. The financial reporting, analysis, projections, observations, and other information contained herein are, and must be construed solely as, statements of opinion and not statements of fact or recommendations to purchase, sell, or hold any securities. NO WARRANTY, EXPRESS OR IMPLIED, AS TO THE ACCURACY, TIMELINESS, COMPLETENESS, MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OF ANY SUCH OPINION OR INFORMATION IS GIVEN OR MADE BY MOODY S IN ANY FORM OR MANNER WHATSOEVER. Each opinion must be weighed solely as one factor in any investment decision made by or on behalf of any user of the information contained herein, and each such user must accordingly make its own study and evaluation prior to investing.

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