Posted by: Josh Lehner | July 1, 2016

The Elephant Graph (Graph of the Week)

A few months ago former World Bank lead economist, Branko Milanovic, released a new book titled Global Inequality. His work has taken the economics profession by storm since. One chart in particular, dubbed by some as the elephant graph, because, well, it looks like an elephant, tells a fascinating story. Branko has a new, very accessible article out today over on VoxEU. I am using that article and chart for this edition of the Graph of the Week.

What the elephant graph shows is “cumulative real income growth between 1988 and 2008 at various percentiles of the global income distribution.” While that’s a mouthful, these economic and income trends in recent decades are important. As discussed below, the elephant graph is also very relevant to our office’s recent work on prime working age Oregon men and women, including some more to come next week.

Branko labels 3 points (A,B,C) which are of particular importance:

The results show large real income gains made by the people around the global median (point A) and by those who are part of the global top 1% (point C).  It also shows an absence of real income growth for the people around the 80-85th percentile of the global distribution (point B).

Branko goes on to explain which populations are at points A, B and C. “Nine out of ten people around the global median [point A] are from Asian countries, mostly from China and India. These gains are not surprising, given that Chinese and Indian GDP per capita has increased by 5.6 and 2.3 times, respectively, over the period… Such dramatic changes in relative income positions, over a rather short time period, have not occurred since the Industrial Revolution two centuries ago.”

Point C consists of the global top 1%, which is “overwhelmingly people from the advanced economies – one half of the people in that group are Americans…”

Point B has been getting the most attention because it shows, effectively, no income growth in recent decades. And the fact that “Seven out of ten people at that point are from the ‘old rich’ OECD countries. They belong to the lower halves of their countries’ income distributions, for in effect the rich countries’ income distributions start only around the 70th percentile of the global income distribution.”

This gets at the overall stagnating median household income figures seen in the U.S. and here in Oregon too. It also gets at the lower inflation-adjusted wages for prime working age adults without a college degree, job polarization and the like. Again, I will have a bit more on this next week from an Oregon perspective.

What Branko’s elephant graph clearly shows is how these trends compare to the global changes seen in recent decades. In his article today, and in various book reviews you can find online, the discussion broadens to talk about inequality and the impact of globalization and the like, in addition to some political ramifications of these trends. However, for today I just wanted to highlight this new important work and how it helps place some trends we’re seeing in the U.S. and here in Oregon in a global perspective.

Posted by: Josh Lehner | June 30, 2016

Prime Working Age Oregon Women

Following our look at labor force participation rates (LFPR) and employment opportunities for prime working age males in Oregon the other day, today we will focus on female participation. The patterns shown below are both different from a 60 year perspective but similar if we focus just on the past 15 years or so.

Female participation differs significantly in the sense that it rose considerably in the 1960s, 1970s and 1980s as women entered the workforce in much greater numbers than historically had been the case. These gains are seen across the educational attainment spectrum. Female participation, while higher than a generation or two ago, still remains lower than male participation. Nationally, in 2015 prime working age women had a LFPR of nearly 74% while men were just over 88%. According to the Oregon Employment Department’s report on participation, it looks like the male-female gap is somewhat smaller here in Oregon.


Where male and female participation trends look similar is in the fact that nonparticipation among prime working age adults has been rising in the past 15 years. It is certainly true that we are seeing in increase in stay-at-home moms, as our office’s report shows (and looking at the most recent data these trends have continued).

However, given lower birth rates and the like, the uptick in stay-at-home moms is not quite as apparent when looking at all women in terms of why LFPR has been decreasing. Overall, much of the gains in nonparticipation are due to reasons other than staying home to take care of the kids, even as that remains the single largest reason cited. Since 2000, nonparticipation rates are up due to increased school enrollment (1.0 percentage point), retirements/other (1.2 ppt), illness or disability (1.4 ppt), those who could not find a job (1.8 ppt) and taking care of home or family (2.4 ppt).


The changing labor market and job opportunities likely has a significant impact on participation rates for women, just as they do for men as we noted the other day. This is particularly true among those with lower levels of formal schooling. The last graph shows the employment-population ratio by job type for Oregon women with a high school diploma or less. This is the time series version of the distributional change chart included in the male post.


While low-wage employment opportunities have been rising over time, the decline of middle-wage jobs is equally important for women in the workforce. This is true, even though the conventional wisdom tends to focus on the decline of the blue collar jobs which have traditionally been held by men — construction, manufacturing, transportation, etc. In fact, next week I have some follow-up graphs on middle-wage job losses for prime working age Oregon men and women. Not to be click-baity, but one result even shocked me even as I knew it was probably true.

Posted by: Josh Lehner | June 28, 2016

Prime Working Age Oregon Males

The Oregon economy is nearing full employment, a milestone not seen since 2000. According to our office’s Total Employment Gap, the one remaining part that is not fully healed is the participation gap. This measures the difference between the actual labor force participation rate — the share of adults with a job or looking for work — with a demographically-adjusted version to take into account the aging Baby Boomers. The underlying question is how much slack is left in the economy? The reason being is that once the slack is gone, one can expect the economy to begin to transition to a more sustainable rate of growth in the future.

So it was with great interest that the White House Council of Economic Advisers released a new report focusing on participation among prime working age males, those between 25 and 54 years old. One reason this group is analyzed is they have historically had the highest participation and employment rates in the economy. This group is also seeing long-run participation declines for much of the past 50 years. This matters for both macro reasons, such as potential economic growth, and micro reasons:

A large body of evidence has linked joblessness to worse economic prospects in the future, lower overall well-being and happiness, and higher mortality, as well as negative consequences for families and communities.

To help our office better understand these changes, what follows is an abridged version of the CEA report using Oregon data.

First, there have been considerably different outcomes among various subgroups within the prime working age population. One key aspect is educational attainment. Those with a college degree have not seen their employment or participation rates decline nearly as much as those with less formal schooling. Oregon’s patterns look nearly identical to the nation overall.


Next the CEA tries to understand what is driving these trends by analyzing supply side and demand side issues in addition to broader institutional changes. Their results show that while supply issues are real, they alone cannot explain the timing nor the magnitude of the LFPR declines. Demand side issues fit the data better.

On the supply side, participation among prime working age Oregon males is down 6 percentage points since 2000. This is a big drop. There has been a large increase in those claiming they are not looking for work due to being ill or disabled. This increase accounts for 60% of the participation rate change overall, on net. However, what is interesting to note is that this increase has not been accompanied by a corresponding increase in those actually receiving disability payments. There is a big disconnect here that may be a little hard to reconcile. However the data makes clear that the increases in those claiming disability as the reason for not working is many times larger than the actual increase in those in disability programs.


To the extent that these individuals are permanently gone from the economy, it does not necessarily matter if what they claim and what they do are different. A smaller labor force results in slower economic growth moving forward, everything else equal.

What the CEA does find is that demand side issues fit the LFPR declines better overall. This means that the fewer job opportunities for prime working age males, particularly those with less schooling, leads to lower participation rates. This is both good and bad news. A stronger economy that creates more jobs will employ more people. However to the extent that the skill sets of those out of the labor force today do not match the demands of the new jobs, a stronger economy alone cannot help these trends.

Among Oregonians with a high school diploma or less, middle-wage jobs have declined in recent decades. This is true both as a share of the economy and in the outright number of such jobs. Of course we have known about job polarization and its impact on the Oregon economy for some time now. However, the losses of blue collar jobs is particularly pronounced among this demographic group. While some have found work in either high- or low-wage occupations, the vast majority of this adjustment has been to drop out of the labor force entirely.


Part and parcel with these trends is the flat to declining wages for those with a high school diploma or less. Two generations ago, wages were somewhat similar across the educational attainment spectrum, both nationally and in Oregon. This widening gap is due to both wage gains for college-educated workers and also wage declines for those with a high school diploma or less. Additionally, the CEA report found that states with higher wages for those in the lower part of the income distribution saw higher LFPR overall.PAMwages

The falling participation rate is a discouraging economic trend, particularly among the prime working age population. In recent years our office has researched various portions of the LFPR decline, including the increase of stay-at-home parents, and to what extent the declines are more likely to be cyclical vs structural. This last part is the most important for our office and the outlook both in trying to time the transition to more sustainable rates of growth and also the size of the potential labor force and economy in the future.

For businesses, we know that as the economy gets closer to full employment, finding quality workers is certainly more challenging. Businesses must cast a wider net and also pay higher wages to attract and retain the best workers. This is happening today, in Oregon in particular where our LFPR is rising quickly and wage growth outpaces the typical state. Of course there is still room for further improvements too.

The CEA report itself explore more in-depth the impact of spousal income, public sector benefits, poverty rates, international comparisons and flexible labor market policies. The report ends with a section on policies to try and boost participation, for those interested.

Posted by: Josh Lehner | June 23, 2016

Oregon Income, A Discussion

A lot has been made of and discussed about the fact that Oregonians have lower incomes than the nation overall. However, I find myself reaching for various measures of income when the need arises, or to answer specific questions. Are we talking about wages, or about household income, or about the potential tax base for revenues? There is no one measure to rule them all. Each has both pros and cons about its usefulness, depending upon the question being asked. Below I have pulled together a handful of income measures to show how Oregon stacks up. Interestingly enough, the differences shown below are pretty important. Note that the graph shows Oregon’s income by category as a share of the national figure. Values below 100% indicate that Oregon has lower incomes than the nation.


Clearly there is a wide range of outcomes when looking at the data. Median earnings for full-time workers in Oregon are just a notch below the national figure, however the state’s per capita income is 10% below the national figure. There are some important reasons for why these patterns happen, based on the underlying demographics, economy, share of full-time vs part-time workers and the like. However I want to focus on two measures in particular: per capita personal income and median household income.

Per capita personal income is a measure that simply adds up all the personal income in the state and divides by the population. Oregon’s per capita personal income has eroded over time, relative to the nation, as research from both the business community and the Employment Department has documented. (Quick aside: our average wages have not eroded in a similar manner, which is an important distinction) I would argue that per capita personal income is a very important measure when discussing tax revenues, or the potential tax base. It shows the average ability to pay, more or less, of a given region’s residents. However it is also an average and susceptible to both demographic shifts and to the distribution of the incomes across the population. As such, even though per capita personal income is widely cited, it is probably not the best measure to use when talking about how Oregonian incomes compare to the nation overall. I am not saying, however, that per capita personal income is not an important measure, rather that it has a time and place to be used.

Median household income is my go-to measure when someone asks to compare incomes across regions. The simple reason is that, by definition, the median household income represents the typical household, so it is much less susceptible to outliers, distribution issues and household/family/population composition. In my view, it is a more accurate reflection of what the typical Oregonian earns.

Oregon’s median household income has largely tracked the national figure in recent decades, which is to say it is unchanged or declining after adjusting for inflation. Outside of the timber industry’s peak and restructuring in the 1970s and 1980s, Oregon’s median household income has pretty consistently been 2-3 percentage points lower than the national figure.


What is really interesting is to look at the distribution of household incomes in Oregon relative to the nation. The final graph does just this for incomes across the entire distribution, based on percentiles. For example, Oregon households at the 20th percentile earn about $21,000 while a U.S. household at the 20th percentile earns $21,700. As noted in the graphs above, the median Oregon household income is about 5 percent below the national median ($51,100 vs $53,700).


What really stands out is the widening gap at the highest income levels. To be in the Top 5% of household income in Oregon it takes roughly $185,000 per year, whereas to make it nationally it takes roughly $207,000 per year, or a gap of 11 percent. In fact, the Oregon-US gap among the highest 10% of incomes is twice that of the bottom 90% of incomes. Why exactly this is the case is not entirely clear. However we do know that Oregon is not a financial center, so we miss out on some of those really high-paying occupations. It is also true that our high personal income tax rates likely play a role as well in deterring some, but not all, high-income households and businesses from locating or operating in our state. But what is very clear is the fact that the widening gap in incomes at the top end of the spectrum mathematically weighs on average incomes, but not medians. Go back to the first chart and see how much further away from the national figures the averages are relative to the medians. The differences there are being driven by the widening gap at the top.

Is this a problem? Well, that depends upon the question you are asking.

A big thank you to Kanhaiya, our state demographer, for pulling the historical Census data and the distribution figures for the latest ACS!

Posted by: Josh Lehner | June 14, 2016

A Note About The Housing Trilemma

The response and feedback on the Housing Trilemma has been amazing this past week, if not a bit overwhelming at times. A big thank you to those of you sharing, asking questions and providing feedback and thoughts on improvement. I really appreciate it.

Unfortunately in my effort to keep the original post a manageable length, I left out a few additional details that would have helped the public conversation this past week. I want to clarify three things regarding the placement of metros on the Venn diagram, the Midwest/Great Plains, and also the quality of life measures.

First, while only 15 metros were listed on the Venn diagram, every single metro does fit on it somewhere. I only used a few representative examples for each part of the diagram. This has been a point of confusion, due to my failings of explaining that originally.

For example, while I mention that 8 individual metros rank among the top half along all three dimensions, I only show 3 metros in the middle part of the diagram. Additionally, New York slots right in between San Francisco and Portland and Kansas City is just to the right of Oklahoma City in the original work. From a broad regional perspective, here is how the Venn diagram looks. As you can see, these regions and the select metros listed originally line up accordingly.


Second, the Midwest or Great Plains do not generally knock any particular dimension of the trilemma out of the park. Rather, they score very solidly along each dimension. That is why they are placed in the middle, or overlapping region. This does not necessarily mean they are the best place to live in the country — that is up to you! — just that the underlying data indicates their placement is probably higher, possibly significantly so, than the conventional wisdom suggest.

Third, there are two quality of life variables used. One comes directly from the academic literature. Professor David Albouy has conducted some great and fascinating research on metropolitan areas, including both quality of life measures and housing cost differentials (both used in the trilemma work). It is a composite measure that looks at the characteristics of a place for which people are willing to pay more to live in, after controlling for incomes, essentially. The underlying variables include things like weather, distance to the ocean, crime, air quality, bars and restaurants, and arts and culture. The second variable used is household purchasing power, effectively getting at how far one’s dollar goes in a particular place after adjusting for the cost of living. Combined these measures get at nice places to live where you can afford to do so. They are not perfect measures, of course, but do provide fairly reasonable rankings across all 100 metros. The Great Plains/Midwest metros tend to rank in the 30-50 range.

Posted by: Josh Lehner | June 8, 2016

The Housing Trilemma

Every city wants to have a strong local economy, high quality of life and housing affordability for its residents. Unfortunately these three dimensions represent the Housing Trilemma. A city can achieve success on two but not all three at the same time. Underlying all of these tradeoffs are local policies as well.

Inspired by Kim-Mai Cutler and Cardiff Garcia, I set out to try and quantify the Housing Trilemma across the nation’s 100 largest metropolitan areas. It turns out to be very real. Just eight rank among the top half for all three dimensions of the Housing Trilemma. None rank among the Top 20 in all three. Unless you prefer living on the Great Plains, that list of eight metros lacks sizzle*.

Update: All 100 MSAs fall within the Venn diagram below. The metros listed are to show some individual metros that are representative of each part of the diagram. For example, New York City slots in right between San Francisco and Portland. Kansas City is just to the right of Oklahoma City. And so forth. Email me if you would like a version with your metro on it.


The reason these tradeoffs exist is mostly, but not entirely, due to market forces. People want to live in cities with a strong economy and high quality of life. Increased demand for housing leads to higher prices and lower affordability. Nice places to live get their housing costs bid up due to strong demand. The opposite is true as well. Regions with underperforming economies and a lower quality of life do have better affordability.

Below are the Housing Trilemma graphs for Portland, Houston and Youngstown to give a few examples of how each city compares to the nation’s 100 largest metros. Note that the bars represent percentiles, or rankings. This is to make the graph easy to read and visually intuitive. The longer the bar, the better a particular metro ranks on that measure. Click here for an interactive version** where you can pick and choose any metro to examine and/or download the data. Go to the “graph” tab and choose a metro from the dropdown menu. Take it for a test drive. The specifics of each metric are shown at the end of the post.

UPDATE: Some are noting issues with the interactive version. Download in Excel here: HousingTrilemma

Trilemma-PDX Trilemma-HoustonTrilemma-Youngstown

Google Docs Version  or Excel Download: HousingTrilemma

Clearly a few patterns emerge. In particular the popular metropolitan areas stand out, not least because their eroding housing affordability is constantly discussed. What you could call the cool city profile is seen in the Denvers, Portlands and San Franciscos of the world. In a way, they are victims of their own success. Their strong regional economy and high quality of life do come as the cost of lower housing affordability.

Yet even among this group, affordability does vary. Portland is an extreme case with significantly more households cost-burdened and a lower vacancy rate than nearly all other metros in the nation. This impacts renters the most, including younger households and those on fixed incomes.

For these popular metros, more construction is required, but that alone is not enough. Just look at Austin, TX. The region has a very strong economy and high quality of life. Despite leading the nation’s largest metros in new construction, Austin is only able to reach middling affordability. Austin’s home prices, while lower than Portland’s or Seattle’s, are still relatively high and half of all renters are cost-burdened. Increasing construction is able to help with broad, regional affordability, but cannot fully offset the premium required to live in a popular place. In addition to building more homes, targeted programs are also needed to help less fortunate neighbors bear these costs.

The housing trilemma is real. Tradeoffs are inevitable. Here in Portland and the Northwest more broadly, we are fortunate enough to have a good economy and desirable quality of life. We should work to maintain these successes. However, eroding affordability in Portland does not have to be a permanent trend. Increasing construction to match a growing population and strong assistance programs are needed.

Here are the exact measures used.


* Full disclosure: I am from the Great Plains and many of my relatives still live there. However, my wife likes to joke that it’s a great place to be from. These metros usually don’t knock it out of the park on any particular measure, however they are successful and do rank relatively well when compared to the rest of the nation’s largest metros.

** Apologies for the external dataviz link. Having difficulty embedding the work on our site. Let me know if you have any questions.

Posted by: Josh Lehner | June 3, 2016

Oregon Economic and Revenue Forecast, June 2016

This morning the Oregon Office of Economic Analysis released the latest quarterly economic and revenue forecast. For the full document, slides and forecast data please see our main website. Below is the forecast’s Executive Summary.

On the backs of the consumer and the strengthening labor market, the U.S. economic expansion continues. Weakness and uncertainty remain in terms of the global economy, financial markets and the goods-producing industries. However, as the U.S. economy enters the seventh year of expansion, including the longest string on monthly job gains on record, the outlook remains positive. The ongoing job gains and wage growth are pulling workers back into the economy and measures of slack, or underutilization, show ongoing improvements.

Oregon continues to see full-throttle rates of growth. Job gains are outpacing the typical state as are wages for Oregon workers. The state’s economy is quickly approaching full employment, or a healthy labor market. Such a milestone has not been seen since 2000. Encouragingly, underemployment, or those involuntarily working part-time in Oregon is back to pre-Great Recession rates. Given the ongoing economic strength in Oregon, the economic outlook has been raised relative to recent forecasts. The state is now expected to maintain these full-throttle rates of growth through the end of 2017 before longer-run demographics weigh on the outlook.

Absent the state’s new minimum wage law, passed during the 2016 legislative session, the upward revision to the employment outlook would have been even larger. While the impact is relatively small when compared to the size of the Oregon economy, it does result in approximately 40,000 fewer jobs in 2025 than would have been the case absent the legislation. Our office is not predicting outright job losses, however we are expecting somewhat slower growth. Low-wage workers receiving raises in the near term boost incomes. Over time, however, employers will adjust by increasing worker productivity, possibly via capital for labor substitutions.


With the first income tax filing season of the 2015-17 biennium now behind us, Oregon’s General Fund revenue collections remain on track with what was expected when the budget was drafted. Personal income tax collections continue to expand at a healthy pace as a result of strong job growth and wage gains.  Like the overall economy, Oregon’s revenue gains are among the nation’s strongest, but also, they have not come as a surprise.

Personal income tax collections during the filing season came in roughly the same size as last year. However, current collections reflect the payout of kicker credits. If not for the kicker, this season’s collections would have been $300 million larger.Kicker16

Corporate tax collections have started to contract in recent months. Nationwide, corporate profits are falling, largely due to rapid appreciation of the U.S. dollar, and struggles among energy firms and other commodity producers.  Even so, corporate tax collections remain large relative to historical norms. Corporate tax revenues are expected to exceed the 2% kicker threshold by $10.4 million, generating a kicker amount of $32.3 million.

In addition to healthy General Fund revenue growth, Oregon Lottery sales have been very strong as well. Recent collections have consistently come in above expectations. The 2015-17 Lottery outlook has been revised upward as a result. However the forecast for future biennia has been lowered as the Cowlitz Tribe casino, scheduled to open in spring 2017, is being included in the outlook for the first time.

Although General Fund revenues have been tracking very close to expectations to date, the outlook for revenue growth during the upcoming 2017-19 biennium has become somewhat stronger. However current rates of growth are not sustainable indefinitely. As the economy reaches full employment, growth will transition to a more sustainable, long-run path. Over the 10-year forecast horizon, Oregon and other states will face considerable downward pressure on revenue growth as the baby boom population cohort works less and spends less. Revenue growth will fail to match the pace seen in the past.

See our full website for all the forecast details. Our presentation slides for the forecast release to the Legislature are below.

Posted by: Josh Lehner | May 31, 2016

Life Cycle Housing Costs in Oregon

At a recent House Committee on Human Services and Housing, Representative Taylor asked me whether or not the people moving to Oregon, and Portland in particular, can afford to do so? In other words (my words, not hers), do they know what they are getting into regarding housing costs? I hemmed and hawed like any good economist (on one hand…) but her question stayed with me. So I dug into the underlying Census data to answer it the best I could. It turns out that yes, the new young migrant households moving to Portland can afford the rent. Rather, their incomes are effectively the same as the existing young rental households in Portland. Thus the current residents and the new residents can afford, or not afford, the rent to the same degree. (See the addendum at the end for more.)

However, Representative Taylor’s question brings to mind some recent research I’ve been doing regarding generational differences in Oregon. How do employment rates, educational attainment, and the like for the Millennials compare to previous generations in our state? However this research initially began by looking at housing costs over one’s lifetime and then by age cohort. A California version of the graph below sparked this research project. (Also, Joe Cortright at City Observatory has a great primer on lifecyle effects vs generational effects.)

How you read this graph is that each colored line represents an age or birth cohort. These are really 5 year groups, so the 1960 cohort is people born between 1958 and 1962, for example. As you move from left to right, the graph shows the median housing costs as a share of income for rental households across the state. The higher the line the more income is spent on housing.


While it is true that younger households always spend more on housing than those in their prime-working and peak-earning years, the biggest trend that stands out is each successive generation in Oregon spends a larger and larger share of their income on housing. The same is true for homeowners and this is also true in California. This is entirely due to higher housing costs and not due to lower incomes. The typical rental household headed by a 30 year old in 1980 earned $34,000 adjusted for inflation. In 2010 a similar 30 year old rental household earned $34,800. However moving from the green or gray line (Baby Boomers) to the blue line (young Gen Xers and older Millennials) represents an increase of 6 percentage points of income spent on housing (19% to 25%). This translates into the equivalent of $175 per month increase in rents. The gap so far is even larger for the 1990 cohort thus far into their adult lives, although they are also seeing lower incomes since they came of age during the Great Recession and its aftermath.

Again, this is part of a larger research project I’ve been doing that compares and contrasts both life cycle and generational trends in Oregon over the past 40 years. I find it informative to know where we’ve come from in hopes that we can better understand where we are going regarding some of these big, mostly economic trends. In no way, shape, or form is this intended to be pro or anti any generation, even though I know there is quite a bit of that on the internets, hence my disclaimer.

Addendum: Back to Representative Taylor’s question about whether new residents can actually afford to move and live in Oregon. At the hearing I did mention that we get a mix of those using moving van lines which likely have a job and the DIYers with U-Hauls which probably do not. I also talked about how 20- and 30-somethings in Portland have the same employment rates (EPOP) as the typical large metro in the nation. The local economy is able to absorb and integrate the new residents.

However, in looking at the specific data it turns out that new, young rental households in Portland earn the same amount of income as the existing young, rental households. Thus they can all afford, or not afford, housing to the same degree. However, it is true that folks moving from outside of Oregon do have slightly higher incomes, but they also pay slightly higher rents. If it’s not just due to the margin of error, I think there are clear reasons for these patterns.

First on the rent. People who move are subject to the current market rates for housing, while those who do not move are likely in a better spot either location-wise of financially. If the rent and neighborhood are good, or even acceptable, why move until necessary? Second, one key aspect of migration in recent decades is the fact that higher migration rates are associated with higher levels of educational attainment. The influx of migrants always have more schooling, which typically translates into higher incomes. I suspect this differences in the mix of households is the reason for the higher incomes of migrants.


Note: I used the 2014 ACS 5 year estimates here to get a larger sample size (n=3,999). The 2014 ACS 1 year estimates showed, broadly, the same patterns but the sample size was just 821. When you start decomposing that into out-of-state migrants, the sample shrinks to just 74 individual households with 15 from California. To the extent that the patterns in 2016 differ from 2014, then these results may not hold of course.

Posted by: Josh Lehner | May 25, 2016

Housing Does Filter

Most new construction in recent years has been at the top end of the market. This is partially due to that’s where the numbers pencil out best for developers but also because that’s where the strongest growth in households has been, in the $100,000 per year and over groups. The majority of the population cannot afford new construction today, but this has largely been the case historically as well.

However, over time housing does become more affordable as it depreciates. This is called filtering and has been a surprisingly contentious topic within the housing discussion lately. The key is that filtering does not happen overnight. It is very much a longer run process. Filtering is also one of the major ways to provide reasonably priced workforce housing for those making in or around the median family income.

To show how filtering works and put some local numbers to it, I have pulled together a couple graphs below, along with borrowing some work from ECONorthwest as well. In recent weeks I have had the opportunity to co-present with both Lorelei Juntunen and Mike Wilkerson from ECO on housing at a planners conference at Metro and the state’s House Committee on Human Services and Housing, respectively.

First, a simple graph showing median rents in the City of Portland and the overall MSA by year of construction. Clearly newer construction is more expensive and housing built in the 1960s and 1970s is the least expensive. Ownership patterns are very similar. Note that the oldest homes are also more expensive. This is largely due to the fact that only a fraction of the homes built 100 years ago remain. Those that do are generally of the best quality, have been remodeled and taken good care of.


Next is a very useful graphic from ECONorthwest that shows how filtering works. It is important to keep in mind that filtering is a market rate housing process and that the supported environment operates differently. Lorelei also noted that it is not to be expected that new luxury construction filters all the way down to purely affordable housing over time. Luxury housing starts at such a high price point that filtering over a few decades can only lower costs so far. Building at a wider range of price points is also needed.



So you’re asking yourself, “OK, but can we actually see this in the data?” I’m glad you asked. Yes, yes you can. What I have done is look at apartments built in the 1970s in Clackamas, Multnomah and Washington counties, or the heart of the Portland MSA.

According to the 1980 Census data, these 1970s-built apartments rented at prices about 11% above the overall market. That means the newer construction in 1980 was more expensive than 2/3rds of all rentals, which makes sense because new construction is almost always more expensive. Fast forward to 2014 (the latest available ACS data). Those same 1970s-built apartments now rent at prices 6% below the overall market. That means they are priced higher than about 40% of the market today. Clearly the 1970s-built apartments have filtered down within the housing market over the past 30+ years.


A key question is whether or not filtering is enough to achieve better affordability overall. The answer is no, or at least not when we are facing a supply shortage of housing. Filtering does certainly work and it does help. However, to the extent that housing is under-built relative to population growth and demand, filtering will be slower and take longer because there are not enough units to go around. That is why one linchpin to the filtering process is to continuously add housing supply, particularly in popular and growing cities and regions.

Lastly, I would like to highlight some research being done right now at the University of Oregon. Two economic students are working in a community issues capstone class to put a number to the filtering process in Eugene (Lane County) where there has been a big increase in new multifamily construction in recent years, mostly for students. How are all these new, more expensive units going to impact the overall market in the coming years and decades? When that work is finished, I will share the results because it is very interesting and timely research.

Posted by: Josh Lehner | May 19, 2016

Willamette Valley Beer Production

It’s American Craft Beer week right now so I thought I’d show a few graphs of beer production in the Willamette Valley. The data comes from OLCC reports which show only beer produced and sold in Oregon. Out-of-state sales/distributions from Oregon breweries are excluded. This has an impact on the largest brewery trends, but hardly any for the majority of the state’s breweries.

Probably the biggest trend that stands out is that the growth in recent years is entirely due to the newer start-ups. At some point a brewery effectively saturates the local market and it is hard to increase sales and distribution within the state simply because a given brewery’s product is in every store and on tap in nearly every bar or restaurant. This is most easily seen in the state’s legacy breweries like a Deschutes or a Widmer. Outside of, maybe, the specialty stores and taprooms, when was the last time you went into an eating or drinking establishment and didn’t see Deschutes or Widmer on tap? While considerably younger, this same situation applies to Ninkasi as well. After years and years of nearly exponential growth, Oregon production and sales for Ninkasi have slowed.

OK. Onto the graphs. Let’s first start with the biggest breweries in the Willamette Valley. One thing to note here is the scale used in the graph. Hop Valley produces as much beer for Oregon sales as every other brewery in the Valley combined, other than Ninkasi of course. Ninkasi itself is more than 50 percent larger than Hop Valley. So these breweries dominate regional beer production (and are among the biggest/most successful in the state as well).


The second graph shows the other Eugene or Lane County breweries. Here the growth due to the recent start-ups is very apparent.


Heading north, Mid-Valley beer production shows a more steady increase over the past decade. A new brewery opens about every 1-2 years and drives regional production and sales higher.


Further north, the Salem regional production is shown below. There are a few notes about the Salem data. First, Gilgamesh is the largest Willamette Valley brewery outside of those first three Eugene ones, and continues to grow and expand. Second, Seven Brides disappeared in the data over the past year. As far as I can tell this is a data issue only, but does skew/mislead the overall regional trends.


As slow progress continues to be made on our office’s start-up brewery report, additional regional graphs like this will follow in the coming months. The big picture trends are evident across the state. Start-ups are driving the growth. Larger breweries are growing their sales into other states and even internationally. As such, brewing is increasingly a traded-sector industry with a wide geographic footprint within the state. While Bend, Eugene and Portland may be best-known for their breweries, every region of the state has award-winning breweries and growing production and sales.

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