Introduction

The year is drawing to a close, and by many measures 2016 was the best year for housing in a decade. Back in May11 See: http://lenkiefer.com/chartbooks/may2016/index.html I shared some trends on housing markets in a document similar to this. Now that we have nearly a full year’s worth of data, let’s see how housing and mortgage markets did in 2016.

I’ve been tracking trends in the housing and mortgage market throughout the year, sharing many different data visualizations22 On my blog at http://lenkiefer.com I have shared R² code for most of the visualizations you’ll see in this post. Check back there for more updates in future. Let’s look back on this year’s best data visualizations and what they tell us about key trends.

Mortgage rates

If you’ve been following me, I’ve spent a lot of time talking about mortgage rates. Just about every week I produce a number of graphs showing trends in mortgage rates. Because most homebuyers use a mortgage33 According to the American Community Survey in 2015 about 63% of homeowners have a mortgage: https://factfinder.census.gov/bkmk/table/1.0/en/ACS/15_1YR/DP04., movements in mortgage rates have a significant impact on housing demand. Rising rates lower homebuyer affordability and price some prospective buyers out of the market.

Mortgage rates on 30-year fixed mortgages started the year at about 4%44 See http://www.freddiemac.com/pmms/pmms_archives.html for details and fell for most of the year. But starting in the fall and accelerating after the U.S. election on November 8th rates began to rise. As of the last week of 2016, 30-year mortgage rates averaged 4.32 percent.

The table below shows the history of monthly average 30-year fixed mortgage rates from 1971 through 2016, while in the margins I include several of my favorite visualizations for rates. You can read more about these figures, find more examples, and get sample code to create them here, here, and here.

⊕Some of my favorite mortgage rate visualizations:

	1st Quarter			2nd Quarter			3rd Quarter			4th Quarter			Annual
30-year Fixed Mortgage Rates in Percentage Points
	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Avg
1970s
1971	NA	NA	NA	7.31	7.42	7.53	7.60	7.70	7.69	7.63	7.55	7.48	7.54
1972	7.44	7.32	7.30	7.29	7.37	7.37	7.40	7.40	7.42	7.42	7.43	7.44	7.38
1973	7.44	7.44	7.46	7.54	7.65	7.73	8.05	8.50	8.81	8.77	8.58	8.54	8.04
1974	8.54	8.46	8.41	8.58	8.97	9.09	9.28	9.59	9.96	9.98	9.79	9.62	9.19
1975	9.43	9.11	8.90	8.82	8.91	8.89	8.89	8.94	9.13	9.22	9.14	9.10	9.05
1976	9.02	8.81	8.75	8.73	8.77	8.85	8.93	9.00	8.98	8.93	8.81	8.79	8.87
1977	8.72	8.67	8.69	8.75	8.83	8.86	8.94	8.94	8.90	8.92	8.92	8.96	8.85
1978	9.02	9.14	9.20	9.36	9.57	9.71	9.74	9.79	9.76	9.86	10.11	10.35	9.64
1979	10.39	10.41	10.43	10.50	10.69	11.04	11.09	11.09	11.30	11.64	12.83	12.90	11.20
1980s
1980	12.88	13.04	15.28	16.33	14.26	12.71	12.19	12.56	13.20	13.79	14.21	14.79	13.74
1981	14.90	15.13	15.40	15.58	16.40	16.70	16.83	17.29	18.16	18.45	17.82	16.95	16.64
1982	17.48	17.60	17.16	16.89	16.68	16.70	16.82	16.27	15.43	14.61	13.82	13.62	16.04
1983	13.25	13.04	12.80	12.78	12.63	12.87	13.42	13.81	13.73	13.54	13.44	13.42	13.24
1984	13.37	13.23	13.39	13.65	13.94	14.42	14.67	14.47	14.35	14.13	13.64	13.18	13.88
1985	13.07	12.92	13.17	13.20	12.91	12.21	12.03	12.19	12.19	12.13	11.78	11.26	12.43
1986	10.89	10.71	10.08	9.94	10.14	10.68	10.51	10.20	10.01	9.97	9.70	9.31	10.19
1987	9.20	9.08	9.04	9.83	10.60	10.54	10.28	10.33	10.89	11.26	10.65	10.64	10.21
1988	10.38	9.89	9.93	10.20	10.46	10.46	10.43	10.60	10.48	10.30	10.27	10.61	10.34
1989	10.73	10.64	11.03	11.05	10.77	10.20	9.88	9.98	10.13	9.95	9.77	9.74	10.32
1990s
1990	9.89	10.20	10.27	10.37	10.48	10.16	10.04	10.10	10.18	10.18	10.01	9.67	10.13
1991	9.64	9.37	9.50	9.49	9.47	9.62	9.57	9.24	9.01	8.86	8.71	8.50	9.25
1992	8.43	8.76	8.94	8.85	8.67	8.51	8.13	7.97	7.92	8.09	8.30	8.21	8.39
1993	7.99	7.68	7.50	7.47	7.46	7.42	7.21	7.11	6.92	6.83	7.16	7.17	7.31
1994	7.06	7.15	7.67	8.32	8.60	8.40	8.61	8.51	8.64	8.93	9.17	9.20	8.38
1995	9.15	8.83	8.46	8.32	7.96	7.57	7.61	7.86	7.64	7.47	7.38	7.20	7.93
1996	7.03	7.08	7.62	7.93	8.07	8.32	8.25	8.00	8.23	7.92	7.62	7.60	7.81
1997	7.82	7.65	7.90	8.14	7.94	7.69	7.50	7.48	7.43	7.29	7.21	7.10	7.60
1998	6.99	7.04	7.13	7.14	7.14	7.00	6.95	6.92	6.72	6.71	6.87	6.74	6.94
1999	6.79	6.81	7.04	6.92	7.14	7.55	7.63	7.94	7.82	7.85	7.74	7.91	7.44
2000s
2000	8.21	8.32	8.24	8.15	8.52	8.29	8.15	8.03	7.91	7.80	7.75	7.38	8.05
2001	7.03	7.05	6.95	7.08	7.14	7.16	7.13	6.95	6.82	6.62	6.66	7.06	6.97
2002	7.00	6.89	7.01	6.99	6.81	6.65	6.49	6.29	6.09	6.11	6.07	6.05	6.54
2003	5.92	5.84	5.75	5.81	5.48	5.23	5.63	6.26	6.15	5.95	5.93	5.88	5.83
2004	5.71	5.63	5.45	5.83	6.27	6.29	6.06	5.87	5.75	5.72	5.73	5.75	5.84
2005	5.71	5.63	5.93	5.86	5.72	5.58	5.70	5.82	5.77	6.07	6.33	6.27	5.87
2006	6.14	6.25	6.32	6.51	6.60	6.68	6.76	6.52	6.40	6.36	6.24	6.13	6.41
2007	6.22	6.29	6.16	6.18	6.26	6.66	6.70	6.57	6.38	6.38	6.21	6.09	6.34
2008	5.76	5.92	5.97	5.92	6.04	6.32	6.43	6.48	6.04	6.20	6.09	5.29	6.03
2009	5.05	5.13	5.00	4.81	4.86	5.42	5.22	5.19	5.06	4.95	4.88	4.93	5.04
2010s
2010	5.03	4.99	4.97	5.10	4.89	4.74	4.56	4.43	4.35	4.22	4.30	4.71	4.69
2011	4.75	4.95	4.84	4.84	4.64	4.51	4.54	4.27	4.11	4.07	3.99	3.96	4.45
2012	3.92	3.89	3.95	3.91	3.80	3.67	3.55	3.60	3.50	3.38	3.35	3.34	3.66
2013	3.41	3.53	3.56	3.45	3.54	4.07	4.37	4.46	4.49	4.19	4.25	4.46	3.98
2014	4.43	4.30	4.34	4.34	4.19	4.16	4.13	4.12	4.16	4.04	4.00	3.86	4.17
2015	3.67	3.71	3.77	3.67	3.84	3.98	4.05	3.91	3.89	3.80	3.94	3.96	3.85
2016	3.87	3.66	3.69	3.60	3.60	3.57	3.44	3.44	3.46	3.47	3.77	4.20	3.65
Source: Primary Mortgage Market Survey, Average of weekly rates

Factors driving mortgage rates

Many factors drive interest rates, but some of the most significant factors include inflation trends and Federal Reserve policy decisions. If inflation, or even just inflation expectations55 See this recent note from the Federal Reserve on the relation of inflation and perceptions of inflation: https://www.federalreserve.gov/econresdata/notes/feds-notes/2016/inflation-perceptions-and-inflation-expectations-20161205.html pick up, long-term interest rates include mortgage rates will increase. Indeed, part of the reason long-term interest rates rose after the U.S. election was because of anticipated increased inflation66 See e.g. this recent article in the Wall Street Journal http://www.wsj.com/articles/bond-rout-deepens-after-fed-rate-signals-1481794245.

Federal Reserve policy will influence the path of short term rates, as well as inflation and economic growth. There is not a strong short-term link between mortgage rates and federal reserve policy77 see my post http://lenkiefer.com/2016/05/19/mortgage-rates-and-the-fed-funds for some graphs comparing movements in mortgage rates, Treasury yields, and the Fed Funds rate., but over time, short-term interest rate movements tend to drive longer-term interest rate movements.

Let’s consider each of these in turn.

Inflation Trends

I’ve been covering inflation trends throughout this year88 See for example: http://lenkiefer.com/2016/11/21/consumer-price-viz. Recently, inflation has trended a bit higher. Housing and medical care are two areas that are contributing most to recent inflation growth99 The U.S. Bureau of Labor Statistics provide data on the Consumer Price Index.I often like to look at the special aggregate indices prepared by the BLS. Summaries of these data can be found in Table 3 (https://www.bls.gov/news.release/cpi.t03.htm) of the regular CPI new release..

Inflation trends

At the moment, inflation is not that high. The headline Consumer Price Index (CPI), which includes volatile food and energy prices is running 1.7 percent on a year-over-year basis. The Core CPI, which excludes food and energy prices, is rising a little faster at 2.1 percent. These numbers are still pretty low, and haven’t moved up that much in recent months. It seems to be that expectations of future inflation are driving interest rates more than realized inflation.

Fed dots

In addition to the possibility of higher inflation next year, interest rates are moving higher in anticipation of movements in short term interest rates. We can see some of the reason for this by looking at the Fed’s dot plot1010 See my post http://lenkiefer.com/2016/06/22/Make-a-dotplot for more on the dotplot and how to make these plots.

The dot plot is a special chart that shows the distribution of expectations of the Federal Open Market Committee (FOMC) for the federal funds rate. Specifically it captures the views of each individual FOMC member for the following:

Each shaded circle indicates the value (rounded to the nearest 1/8 percentage point) of an individual participant’s judgment of the midpoint of the appropriate target range for the federal funds rate or the appropriate target level for the federal funds rate at the end of the specified calendar year or over the longer run.

The Fed makes the dot plot information available in a handy format here: FOMC materials. For example, the December 2016 projections look like this: ⊕This plot compares movement in the dots over 2016. Throughout the year, as economic conditions changed, the dots moved down. But in December, the dots actually moved up.

FOMC dot plot

The outlook for longer-term rates

Whether or not the Fed raises rates aggressively in 2017 or if inflation ticks up will have a lot to do with how high mortgage rates might go in 2017. At this point, uncertainty is high. But for most of 2016, rates remained extremely low. In fact, for the full year 2016, 30-year fixed mortgage rates had the lowest annual average since at least 1971.

Home Sales, best in a decade

Low mortgage rates in 2016 helped home sales reach their highest level in a decade. Through the first 11 months of the year total home sales (the sum of new and existing homes sales)1111 New home sales are tabulated in a joint release by the U.S. Census Bureau and Department of Housing and Urban Development (HUD) while existing home sales data are reported by the National Association of Realtors. New home sales are estimated with low precision. The confidence interval for monthly changes are typically greater than +/- 10%. Existing home sales are not reported with a confidence interval. is the highest since 2006. Barring an epic collapse in home sales, December will push the annual total in home sales to the highest in a decade.

⊕This animation shows home sales month by month:

Home sales best in a decade

Housing construction

Housing starts have trended higher, but still remain low by historic standards1212 For some more commentary on housing supply, its relationship to population and house price trends see http://lenkiefer.com/2016/05/22/population-growth-housing-supply-and-house-prices. At the link you can see a pretty strong correlation between longer-run house price growth and the gap between population and housing supply growth. Areas where population growth has outstripped housing supply are areas where price growth tends to be stronger..

This plot looks at the level of starts. For most of history, starts averaged about 1.5 million units a year.

Housing supply has been slow to recover. We can see that in the aggregate data, where housing supply is very low relative to historic averages. The graph below shows deviations in monthly housing starts (at an annual rate) from 1.5 million. Historically housing starts have averaged about 1.5 million units, but that’s a fairly conservative estimate for “normal”. The U.S. population in 2016 is significantly higher than it was in the past. All else being equal, that implies we probably need more than 1.5 million units to meet long-run demand. I’ve estimated long-run demand to be closer to 1.7 million.

Monthly housing starts relative to 1.5 million

House price trends

Low mortgage rates help to boost homebuyer affordability, which is good because house prices are growing faster than incomes in most markets. For the full year 2016 house prices will probably grow around 6 percent on a year-over-year basis1313 Various house prices indices have registered around 6 percent year-over-year growth through September and October. Housing markets tend to be quite persistent so annual appreciation will probably be in the neighborhood of 6 percent..

House prices are (just barely) above their pre-recession peak1414 I use the Freddie Mac House Price Index here, but other indices such as the FHFA Index or the Case-Shiller Index also surpassed their pre-2008 peak in the fall of 2016. without adjusting for inflation. Adjusting for inflation house prices are still down about 20 percent from their inflation-adjusted peak.

National house prices are at an all-time high.

In 2016 I wrote several Visual Meditations on House Prices1515 See them at: http://lenkiefer.com/2016/05/08/visual-meditations-on-house-prices where I looked at different visualizations of house price trends.

House prices, incomes and rents

On Twitter I ran a poll on which house price visualization my followers liked best. Their favorite was this one comparing house price growth to rents, incomes, and other prices1616 See http://lenkiefer.com/2016/11/30/hpi-gif for more..

⊕Also consider the ratio:

This visual shows that in aggregate since the 1990s house prices have grown faster than rents and other prices, but below income. Recently house prices in the U.S. have been growing faster than incomes, but at least through late 2016 house price growth has not far outpaced income growth like it did in the last decade.

Global price trends

I also examined trends globally1717 See http://lenkiefer.com/2016/12/10/global-house-price-trends for more.. The graph below shows international house price trends, comparing real incomes to real house prices in several countries.

⊕An animated version for a slightly different set of countries:

Local price trends

I also looked quite a bit at local house price trends this year.

One of my favorite graphics is this chart1818 See http://lenkiefer.com/2016/05/08/visual-meditations-on-house-prices-part2 for more discussion. showing state house price trends.

⊕We can also animate it:

The plot shows the value of the house price index in September 2016 relative to the past 12 months. The color corresponds to the pace of house price appreciation, and the tail represents the range of the index over the past 12 months.

Hawaii has the highest index value (meaning that house prices have grown most in HI relative to December 2000), but the fastest year-over-year growth has been in Washington state. You can see that in the graph by the blueness of the dot and in the length of the tail.

Metro trends

We can also look at metro trends. The animation takes you on a virtual tour of some of the nation’s largest housing markets and shows trends in both the level of prices, and in the annual percentage change in that index:

⊕This chart shows how the distributions of metro area house price appreciation has changed over time. Each dot represents a metro. Code for this plot can be found at http://lenkiefer.com/2016/08/13/visual-meditations-on-house-prices-part5.

The table below has details for individual metro areas. You can search/ filter using the selection boxes. How’s your market doing?

After the best year in a decade what’s next?

Housing markets did well in 2016, can we expect a repeat in 2017? Higher mortgage rates will be a significant challenge for housing markets. Back in 2013 when interest rates rose following the Taper Talk, housing markets slowed. If recent increases in rates persists, we might see a similar slowdown in housing activity in 2017.

Relative to 2013 the U.S. economy is stronger and a tighter labor market is starting to drive wage growth. Three years of low levels of construction and weak household formation have led to more pent up demand1919 See for example http://www.wsj.com/articles/percentage-of-young-americans-living-with-parents-rises-to-75-year-high-1482316203. for housing that will likely keep the pressure on housing markets even with modestly higher mortgage rates. The underlying trends in housing are positive, so we’ll have to see if those factors can overcome the challenge from higher rates. Be sure to follow me and check back for future updates.

A note on code

All of these graphics were made with R2020 I used the Tufte template from Rstudio http://rstudio.github.io/tufte/ and I’ve shared code on my webpage lenkiefer.com. Please reach out to me if you’d like to know more about these graphics or the data I used to generate them. I can be reached on Twitter at @lenkiefer and via email at lenkiefer@hotmail.com.

A look back at housing’s best year in a decade

The year of 2016 in housing dataviz

Len Kiefer

2016-12-31