Weekend long reads (Dec. 5, 2014)

Readers will notice that there hasn’t been much activity here since Thanksgiving. My absence is partly due to traveling I’ve had to do, being engrossed in my new book (The Power Broker by Robert Caro), and other academic obligations, which will continue next week. Nonetheless, I have provided some long reads here as they seem to one of the more popular types of posts. I hope to have the third part of the series on sectoral investment patterns up by the end of next week.

Fracking tantrums


Research and academics

Thanksgiving long reads (Nov. 27, 2014)

Happy Thanksgiving! Here are some articles I have lined up to read over the long weekend. Not all are recent; I’m trying to clear out the reading list.

1. The tech worker shortage doesn’t really exist. Bloomberg Businessweek

2. State unemployment map goes monochrome for October 2014. The Economic Populist. [Not actually monochrome, but close: no state observes an unemployment rate greater than 7.9% (US average is 5.9%), although underemployment is a separate problem. Also contains maps for employment-population ratio by state!]

3. Kuroda turns up the heat on Japan Inc.: turn profits into higher wages. WSJ

4. How the world’s most leveraged hedge fund got away with insider trading. Zerohedge

5. Oil at $75 means patches of Texas Shale turn unprofitable. Bloomberg [Good run-down of the economic-geography of fracking profitability]

6. Public relations and the obfuscation of management errors–Texas Health Resources dodges its Ebola questions. Health Care Renewal

7. Boomers, millennials and interest rates: a muni investor’s perspective. BlackRock blog

8. For middle-skill occupations, where have all the workers gone? Federal Reserve of Atlanta

9. Over at Project Syndicate: economic growth and the Information Age: Daily Focus. Washington Center for Equitable Growth

10. Jeff Henry, Verruckt, and the Men Who Built the Great American Water Park. Grantland.com [Schlitterbahn!]

On the book front, I’ve reading The Power Broker: Robert Moses and the Fall of New York by Robert Caro. I’ve been meaning to read it for a while and then found it at the bookstore, so here I go!

The contemporary context of investment in the United States, part 2: definitions

This post is second in a series on the contemporary state of investment in the US. The first is here. The purpose of this post is to provide some definitions and context. There are three questions: first, what processes does “investment” refer to; second, who invests; and third, what patterns should interest us? To define and identify what investment activity matters (for economic growth and development in the US for the next decade or so), I rely mainly on some of the writings of critical/heterodox economists Hyman Minsky and John Kenneth Galbraith.

What is investment?

There are two common usages of the term “investment”. The first is the buying and selling of shares of companies that are publicly listed on stock exchanges. This set of activities is not the sort of investment I’m talking about in this post. No doubt, the stock market can be a source of capital for companies, which can then be deployed for investment. More often than not, however, the stock market functions as a market for corporate discipline and control (mergers, acquisitions, takeovers). The investment I refer to here is the accumulation of fixed assets (such as capital goods [like machinery], inventory, property, physical structures) for the purposes of generating income.

Let me offer a short digression here. Many would say that the two definitions above reflect a financial definition and then an economic definition of investment. In casual, daily conversation, that might be acceptable. However, if you have read Hyman Minsky then you would be aware that both processes are actually interlinked and co-constitutive. That is, the accumulation of fixed assets happens very much according to what is happening in capital markets (of which stock markets are a sub-set). More specifically, Minsky argues that the financing (particularly when financed through debt) and pricing of capital goods occurs in capital markets. The point is that the capital goods and fixed assets that are used for investment are also financial assets. And because these financial assets are accompanied by ownership claims and are financed, this implies that there are cash flow obligations: the debts that were used to finance capital goods accumulation must be validated. Those obligations are met by splitting off part of the income produced by those assets, either as dividends, interest payments, or perhaps (in dire situations) from the sale of capital goods. To make a long story short, Minsky demonstrates that these arrangements can precipitate a depression in the event that financial asset prices collapse, which he argues is possible if capital goods accumulation is financed in too speculative a manner. Otherwise stated, the capitalist system itself sows the seeds of its own crises. I suggest you read this or this.

Where does this leave our definition of investment? There are at least six elements: it refers to a (1) process of accumulating (2) capital goods, which are simultaneously (3) financial assets that are (4) owned by capitalists/entrepreneurs and (5) might be financed through debt, for the purposes of (6) generating income.

In the next section, I’m briefly going to discuss why (5) and (6) do not always apply but rather depend on who is doing the investing. Nonetheless, I think that the definition here is workable and sufficiently distinguishes this set of activities from the “investing” (asset trading) that commences every day with the ringing of the bell at the New York Stock Exchange.

There are a couple of other points I’d like to add here concerning how investment might influence the larger political-economy. Recently a book was released that contained a number of previously (I believe) unpublished essays by Hyman Minsky (they may have been published in a few academic journals) on the topic of jobs, employment, and welfare. I recommend this one, too, for a general introduction to Minsky’s thought and its application to employment. In the introduction and throughout that book, the reader might notice that the US economy is characterized as observing a “private, high-investment strategy”. I think there are two very important points in that phrase. First, investment is private: it is subject to ownership by individuals, not the state. This point should interest anyone who conducts cross-national comparative research: you cannot compare the investment process in a country like the US, where investment happens by entrepreneurs and households, with a country like China, where capital expenditures are determined largely by committees in state-owned businesses appointed by the (Communist authoritarian) state. It may be a minor point, but I think it is worth bringing up.

The second point is much more important: “high-investment strategy.” What does that imply exactly? The idea is that the US economy in particular generates growth by stimulating investment. That is, more private ownership of capital goods. Such a strategy is executed, in the US at least, by various policies: a tax code that favors capital goods accumulation (incentives for depreciation, tax credits); a favorable business environment (low regulation of business, which decreases the cost of doing business generally); and government contracts that partly underwrite profits in select industries, typically those that require high capital goods consumption (armaments, construction, airlines). Thus “growth” in the US economy is primarily pursued by creating favorable conditions for income generation by businesses.

There are number of problems associated with such a strategy, and I’ll quote the four that are mentioned in that volume on employment by Minsky. These can be found in a summary around kindle location 358-382.

First, a tax code that is geared towards more investment will increase inequality between the owners of capital and labor. For what it is worth, inequality on its own does not necessarily spell economic disaster. For instance, if you have read Thomas Piketty’s book, you’ll know that countries can endure long periods (centuries) of inequality without encountering, say, collapse and ruin. Certainly, there are issues of justice and quality of life that arise from high inequality, but the evidence that inequality might lead to economic and financial crisis is wanting. Politically, I don’t worry about inequality because the President and most American political leaders are not Rockefellers, Morgans, Vanderbilts, Carnegies, Fords, or Hearsts. In other words, the money eventually runs out.

[An aside: one of my favorite economists (Deirdre McCloskey) has recently written a review of Piketty that I suggest everyone read. It’s there on the home page in pdf form.]

Second, the income that accrues to owners of capital can lead to opulent consumption by them and emulative consumption by the masses, leading to inflation. There is a natural experiment here in the period 1964 to 1974 in the US, as employment tightened, defense spending escalated with the War in Vietnam, and the economy enjoyed an investment boom (initiated, by the way, with tax cuts passed during the Kennedy and Johnson administrations).

Third, government spending on defense (contracts to specialized and sophisticated high-technology industries) creates demand for high-skilled, high-wage labor. In turn, this widens the inequality among workers. Again, we can observe the effects of growth in high-technology sectors on wages and skills across occupations by observing the period from 1994 onwards, when the revolution in computer chips and the internet began. This was not totally the result of government spending (in fact, US defense spending dropped off after 1990, leading in part to the recession of 1991), although much of the US advanced technology industry grew out of companies that received defense contracts. Nonetheless, this is a serious problem for worker quality of life and, I would argue, for growth prospects between regions and metropolitan areas.

The final problem Minsky describes of a high private investment strategy is that if the tax code and business environment privilege capital spending, then rising business confidence hence banker optimism will erode lending standards while also increasing the riskiness and speculative nature of investment. The result can be a financial crisis and recession. It is worth noting that the 2008 crisis was not the result of excessive optimism by corporate businesses. Rather, the 2008 crisis was the result of a housing boom and a highly leveraged household and and highly leveraged, speculative, and corrupt financial sector.

At this point, I’ve elaborated enough on what I mean by investment. Now I’m briefly going to outline some key differences between the sources of investment.

Who invests?

I mentioned earlier in my definition of investment that it might be financed through debt and that the purpose of investment is to generate income. I’d like to add some caveats to that with the help of John Kenneth Galbraith.

In a previous post containing links, I had one from the St. Louis Federal Reserve documenting that credit to non-corporate non-financial sectors has remained low following the crisis. That to me was a key indicator of who is able and willing to invest in the current economy. We have at least three major groups here: the corporate sector (AT&T, Wal-Mart, ExxonMobil, DuPont, Microsoft); the household sector (you and me); and the financial sector (banks and lenders big and small). Each of these sectors have very different sources of capital and ways of generating income. The corporate sector, which as you can tell is populated by very large companies that are often structured in what economists would call an oligopolistic market (where they can influence prices of inputs and outputs), gets most of its capital (for the purposes of future investment) from retained earnings. In other words, expansion programs, research and development, development of new products are financed from last year’s profits. These business do not typically take out loans from banks to finance their activities, although they certainly float bonds and stocks as part of their complex capital structures. The main point is that these companies seek to make the supply of capital (like they do for all other strategic costs) a “wholly internal decision” (Galbraith, 2007, 34). Chapters Three and Four in The New Industrial State are the relevant backgrounds for this interpretation.

As such, investment is not necessarily financed through debt. In addition, investment may not happen with the aim of producing income. Galbraith describes that in these large corporate enterprises, the managerial hierarchy is responsible for long-term planning; this includes when and whether to make capital expenditures. The ultimate goal of the corporation, then, is not income or profit generation, but rather the elimination of uncertainty. The corporation seeks stability. The process of investment, we can deduce, will fall in line with how corporate managers attempt to achieve that stability. An oligopolistic market structure allows companies to pursue goals other than the relentless pursuit of profit, contra the neoclassical economics dicta.

In contrast, when American entrepreneurs attempt to launch a business, the financing usually comes from residential mortgages and the purpose is the generation of income (they do not exercise oligopolistic power). A home is an individual’s greatest potential source of capital, save inheritances. Consider how easy it is (excuse me, how easy it used to be) for most people to get a mortgage or to refinance their home; this, too, surely was a reflection of the high private investment strategy (or at least should be treated in policy as such).

Obviously, between the individual entrepreneur and the oligopolistic corporation, there are a lot of businesses that do not have pricing power and that have access to various forms of financing that are not restricted to home mortgages or inheritances. These businesses, which could be termed ‘mid-sized’ and have several hundred employees (let’s say, fewer than 500), and which are typically in manufacturing, transportation, utilities, and related industrial sectors, do enter into debt contracts with banks and other lenders. However, I think that our focus should really fall to entrepreneurs and large corporations. For the former, the reason is that small businesses create a tremendous amount of activity, in terms of jobs and sales. Most small business also fail, so this is a tremendously inefficient set of activities. In the short-term, however, small businesses drive quite a bit of local economic activity while providing a lot of people (not just the small business owners themselves but also the people they hire) with an outlet for social and economic advancement.

In the case of large corporations, the interests of these entities set much of the industrial and social policy in the US, and they are responsible for the bulk of exports and income. Furthermore, municipal and state governments compete quite vigorously over corporations. Local governments offer tax incentives, provide physical infrastructure, train the workforce, etc., partly with the aim of attracting business activity, and therefore tax revenue.

What I’m getting at here is that there is a geography of investment, and two very important features of that geography will be households and large corporations. The financial system is also important in this geography, but these days it is less about the location and activities of banks and more about the location, organization, and prerogatives of special investment funds, like pension or hedge funds. With that, I’ll move on to the final question.

Measuring investment and identifying patterns

I won’t dwell on this point much because instead of telling you what I’m going to do, I may as well just do it. In the next posts in this series, I’m going to present the data I stumbled upon from the Bureau of Labor Statistics for output, savings, and investment. The data is organized by sector, that is, industrial sector following the NAICS codes and also by the divisions suggested above (household, financial, corporate, and others).

The most basic pattern to identify is change over time: which areas demonstrate growth and which demonstrate contraction? There are roughly seven years of annual data, which is not a large sample by any means. There will be some noise.

A subsidiary pattern is relative change. The 2008 crisis marks a point where we can evaluate how credit distress during and after the crisis was distributed between sectors and, consequently, what have been and will be the prospects for investment and therefore economic growth. In other words, we can determine to an extent what sectors are “holding back” growth. Recall that this endeavor was largely touched off by the New York Times article that asked that very question (see previous post). My goal is to further investigate that question.

Link share: geography of a decade of job growth and decline

Check out this very well done interactive graphic from the blog of Austin-based consulting firm TIP Strategies!

I’ve filed this under “Terrible Cartography” (I have no category for the opposite), but rest assured this is the work of professionals.

The contemporary context of investment in the United States, part 1: introduction

The Great Recession (2007-2009) changed the context for investment in the United States in several ways. First, it created imbalances in the economy, in terms of losses and gains between economic (businesses, households, government) as well as industrial (agriculture, manufacturing, services) sectors. These losses and gains can be measured in terms of lost output, including employment. These are imbalances to the extent that contractions in output were unevenly shared across sectors.

Second, the political environment changed as new constituencies and alliances were formed, while others were made more obvious. An example of such a long-standing alliance that became stronger was the relationship between the Federal Reserve and large, globally-competitive financial companies. This relationship was codified in the emergency recapitalization (the TARP) and in the Dodd-Frank law. New constituencies emerged or became more pronounced, for instance as unemployment and homelessness rose, and they reflected a regional character (for the reason that the financial crisis and recession were, in fact, regional crises). These new constituencies and alliances generated pressures for different kinds of policy intervention, with varying success.

And finally, the macroeconomic context changed, given changes or stickiness in the informal rules of investment (such as tax rates, interest rates, the supply of credit). Similarly, economic development through the application of new technologies, discovery and extraction of fossil fuels, and global capital flows also have shaped the macroeconomic context.

Over the next several posts, I’m going to outline the context of investment in the US immediately before and since the financial crash in 2008. I will describe the nature of investment since the crash, with a focus on the distribution of investment activity between sectors (economic and industrial) as well as the nature of investment (private fixed assets: structures, equipment, intellectual property). Finally, I’ll briefly describe the kinds of companies and regions that were poised to reap the benefits of this changing context, and contrast them against those entities that have borne the greatest burden.

The next posts will frame investment in the US with the following specific questions. First, what do I mean when I talk about investment in the United States? I will outline that question by referencing JK Galbraith’s new book (The End of Normal) as well as borrowing some insights from Hyman Minsky. Let me add that I do not mean to advance any kind of coherent theory; that is way beyond my remit at the moment. Rather, I find it useful to identify useful metrics and relationships in the data that can eventually be situated within a wider theory, or can be used to advance or refute other ones.

Second, what are the current obstacles at the geopolitical and national levels to growth in investment within the United States? Off the top of my head, I can think of several important “obstacles”: the process of domestic credit allocation (including interest rates, integrity of too-big-to-fail banks, property development); the cost of raw materials (especially oil and gas); and, military commitments and the general financing of national security. Readers of Galbraith’s book will notice these topics are quite prominent in his account, while I have spent most of my very short academic career focused on the first.

Third, what is the current progress or state of the economic recovery since 2009? There are some subsidiary descriptive questions that point to my thinking here. Which economic sectors have returned to pre-crisis trends in output growth (contribution to GDP) and which remain stalled? Which industrial sectors? How did investment in private fixed assets respond to the crisis and aftermath? What about for investment in structures, equipment, and intellectual property? (If readers want to see what I’m getting at with these questions, take a look at this article from the NYT back in April: http://nyti.ms/1zZEVct; I am essentially expanding this kind of inquiry, which has been, incidentally, the empirical base upon which most of research has been conducted).

My doctoral dissertation advisor liked to say that a solid way to organize an argument follows the formula: what; why; and, so what. The what component here is really, where is investment happening in the USA (both in sector and locational terms). The why seeks to explain the relevant processes that propel the investment we see or hinder the investment we hope for (particularly, why it should be the case that despite there being a real recovery in material terms, there should be such a slow expansion in quality employment opportunities). The so what for me really comes down to distributional fairness. In other words, something that has been on my mind the last few years is whether the parties responsible for the financial crisis and disappointing recovery were the same parties that amortized its costs, or whether there has been a systemic and successful effort to push those costs onto other parts of society. Additionally, I want to explore the durability/sustainability of the investment that is happening. At the end of the day, we all want to be a part of a successful collective endeavor–the US economy. Hopefully I’ll find much to be proud and excited about as I dig through the data. Alternatively, hopefully I can provide some insight into how to rectify the processes that point to the contrary.

Employment update: losses and gains since 2007 recession

In yesterday’s “2:00 pm Water Cooler” links at nakedcapitalism blog (http://bit.ly/1u1lJ9u), Lambert Strether of Corrente blog (http://correntewire.com/) included a Bloomberg map (from September of this year) of the recovery of employment by state since 2007 (http://bloom.bg/1zM4rC5). Specifically, Bloomberg writers purported to depict the ‘uneven recovery in states post-recession’ by showing the ‘percentage difference between a state’s maximum employment in 2014 and its recession high (reached between December 2007 and June 2009).” They sought to highlight only those states where employment remained below peak levels during the recession, coded using a couple shades of red.

As Strether pointed out, it is a rather confusing map, and I don’t think it conveyed the information in the best way. Why construct a choropleth map that only color-codes poorly performing areas? Why focus on individual peaks in employment during the recession? It would make more sense to depict cartographically the employment changes for all the states and to select a uniform starting date.

Being convalescent following my recent surgery means I have plenty of time to create some terrible cartography of my own. My topic here is total employment changes at the state level from 2007 to 2013. Descriptively, the question is: which states bore the brunt of the recession in terms of employment losses and which have experienced a recovery in employment. Before going right for the States, I start by presenting the ratio of employment in December 2013 to employment in December 2007 for the Census divisions (of which there are nine). [All data was drawn from the Bureau of Labor Statistics (http://data.bls.gov/cgi-bin/dsrv?sm)%5D.


Recovery can be interpreted in a couple ways. First, it may refer to replacing lost activity, to the point that employment levels in 2013 equal those in 2007. Alternatively, recovery may refer to a kind of resilience. This term can indicate whether an area has returned to its pre-crisis trend, such that not only has that area recovered employment losses but it has added enough jobs that its employment levels are what would be expected had there not been any output losses. To calculate whether an area indeed was resilient and returned to a kind of equilibrium growth (or whether such a return is even possible!) is beyond my remit for the moment. However, the answer to whether an area is ‘resilient’ in this sense or not has much to do with whether there has been structural change in the economy (labor-saving technology, increases in productivity, further transition out of industry towards services). I highly recommend JK Galbraith’s new book The End of Normal for anyone interested in exploring this question.

As a point of reference, the ratio of 2013 employment to 2007 employment for the nation as a whole was exactly 1. The map (for the lower 48 states; Alaska and Hawaii are part of the Pacific division) shows that the West South Central states (Texas, Oklahoma, Arkansas, and Louisiana—major oil and gas states) performed best, with employment bases roughly six pct larger than they were in 2007. These can be deemed resilient. The West North Central (Great Plains states, where there is also quite a bit of fracking activity) and the Middle Atlantic (Pennsylvania, New Jersey, and New York) were second-best performing. The worst were the Mountain states and East South Central (Kentucky, Tennessee, Mississippi and Alabama), whose employment bases remained three pct below their levels at the end of 2007. These areas are clearly not resilient.

The next map depicts the above ratio of employment levels for all 50 states (maps not to scale). Clearly the Census divisions obscure some important differences within divisions, that is, between states. Census divisions do not always capture coherent economic-units, such as metropolitan areas or industrial districts, particularly in areas along and east of the Mississippi. A more apt unit of analysis for that would be the metropolitan statistical area, however these in turn do not necessarily have a single, coherent governing entity. As such, the US state, with different taxation regimes, varying receipts of federal moneys, bank regulation, local investment and labor force policies, etc, remains an important political-economic unit. The major takeaway, as I see it, is that resilient areas are either oil/gas producing (Alaska, North Dakota and Great Plains more generally, Gulf Coast) or are financial centers (New York and Massachusetts). Meanwhile, the diversified industrial and commercial economies of California, Washington, Virginia, Florida, Georgia, Pennsylvania, and New Jersey remain below their 2007 levels. That is just a hunch. From my academic research, other important factors include exposure to subprime mortgages and the foreclosure epidemic.


The next set of maps show change in employment for two-year increments beginning in 2007.I tried to apportion the states into quantiles, but there were quite a few shared values, and I also wanted to identify some of the outliers. The two-year increments correspond, more or less, with the most recent recession, then a nominal recovery period, and, perhaps finally, a stagnation period. These, incidentally, correspond to the stylized Minskiyan stages of the economic cycle (crisis/crash, recession, recovery, stagnation, economic boom, rinse, repeat). I won’t go into much depth here; I’ll leave readers to gander at these maps to their hearts’ content.




The maps, of course, rely on relative changes. I have also included below a table showing the ten states with greatest absolute employment losses from 2007 to 2009 and then the ten biggest gainers from 2009 to 2013.

Biggest Losers (from 2007 to 2009)
State Chg in employment (000s)
California -1,199
Florida -782
Illinois -409
Texas -403
Michigan -402
Ohio -401
North Carolina -329
Georgia -327
New York -288
Arizona -286
Biggest Gainers (from 2009 to 2013)
State Chg in employment (000s)
California 1,235
Texas 1,128
Florida 583
New York 546
Michigan 331
Ohio 291
Illinois 269
North Carolina 255
Georgia 250
Pennsylvania 230

Though the order in which these states appear varies somewhat, most of the states that lost the most employment also gained much of it back. The exception is Arizona, which lost over a quarter of a million employed workers but did not appear on the gains list. That state’s employment base grew by less than 170,000 from 2009 to 2013. In contrast, Pennsylvania lost close to a quarter of million jobs, but grew by 230, placing it at tenth in the gainer list.

In a previous post, I discussed the differences between employment and job growth. I emphasize here that I have looked at the stock of employed labor, not job growth. The quality of jobs is as important as the quantity, and job growth statistics provide great insights into employee turnover, job stability, and duration of employment. Additionally, I stress the importance of considering the sectoral component, which reveals comparative specialization and thus may indicate how an area is clued into larger financial networks and global supply chains. The utility of these maps is the clarity with which they can generate insights into the material distribution of burdens and benefits following the recession.

Employment update: the job creation meme II, the case of Texas

Note: this post was originally much longer, but WordPress failed me, and I do not wish to spend any more time on this.


In my last post, I discussed some preliminary reactions to one of the job creation memes that circulates in the popular press. In a nutshell, the contention is which groups or processes are responsible for generating jobs—businesses or consumers. Without developing a rigorous argument, I made three points. First, job creation statistics come from businesses reporting the number of employees they have on their payrolls. This point is important because not all workers are on a payroll (undocumented workers; sex workers; black market) and not all businesses accurately report payroll and employee data. So, we’re talking about a specific albeit large part of the economy—the formal, regulated parts, not necessarily cash-only businesses or grey/black market activities.

Second, businesses do not want to create jobs, for at least three reasons: hiring workers (tendering applications, interviewing applicants, training new personnel, etc.) is expensive (firing workers can also be expensive); it is not guaranteed to address its workload stresses; and, it may actually be based on faulty information about business prospects.

Third, ‘job creation’ is a sociological phenomena; we cannot observe ‘job creation’, but really only analyze statistics as they are reported to government agencies. These statistics are only part of the picture. There are qualitative aspects that reveal how job creation happens, such as which kinds of workers are hired (which may be structured by nepotism, cronyism, other forms of corruption, as well educational and skill levels; unionization may also be an important factor), or how businesses recruit and interview applicants (how much businesses spend on recruitment, how much workers spend to make themselves more attractive, through supplementary training, clothing, resume assistance, etc). The process of job creation itself creates costs and allocates those costs unevenly between workers and businesses depending on the characteristics of the company and industry. You could say that ‘job creation’ itself creates jobs, to the extent that human resource departments within companies and specialized recruitment agencies exist to facilitate the process.

Finer points

If you are going to report on job creation statistics, the least one can do is push further into the statistics and describe how the process is happening at lower levels of observation. On this note, there are several questions I would suggest are very important indicators of the nature and quality of job creation.

  • What kind of companies are creating jobs? Are they large/small; young/old; what is their ownership structure (publicly-listed, privately-held, S-corporation, partnership)?
  • What sectors of the economy are creating jobs (agriculture, business services, mining, manufacturing, retail, public sector, etc)? Under what occupational divisions can these jobs be classified (managerial, financial, engineering, legal, sales, administrative, healthcare, etc)?
  • How long do the jobs last? Are they seasonal? What is the rate of the turnover in the industry? If there is high turnover, is it the case that previously-fired employees are returning to old positions (like in manufacturing firms) or is there a regular churn of new employees (like in seasonal retail activities)? What are the job creation rates in high productivity, high value-added industries (such as business and financial services) as opposed to low productivity, low value-added industries? What role does job creation play in productivity and the cost structure of that industry?
  • How do job creation rates differ between similar scales of analysis, such as between major metropolitan areas or states? Within metropolitan areas or states, is there a difference in job creation between component areas (Manhattan versus Brooklyn; San Francisco versus Oakland; Los Angeles versus Orange; Dallas versus Fort Worth)?
  • How does the rate of job creation accord with demographic changes, such as the exit of retiring workers, the entry of new workers, in-migration, and the participation of women (who are more likely to leave the workforce for child-rearing, and possibly return for a variety of reasons)?

I think it is almost pointless to look at national-level job creation statistics for a country like the United States. The more interesting narratives come from specific case studies of industries at certain scales (metropolitan area, region, state). We know that the space-economy is characterized by clustering; the economy can be thought of as an amalgamation of production complexes linked together by networks of supply chains and business services firms. If you want to understand the prospects of a given area, then you must know how that area is inserted into the global economy, by way of its productive enterprises, business services firms, etc. I’m going to sketch out a map of job creation for the case of Texas, specifically its oil and gas sector, using job creation statistics from the Census to highlight the limits of that data. I also want to push past the tired cliche of “job creation” as driven by oligarchs or consumers by highlighting the larger geography in which all of these processes happen to look at the ramifications for workers and cities.

The case of oil and gas in Texas since 2009

I’m going to be as expeditious as possible and so I won’t be putting up comparisons of the oil and gas sector in Texas with other sectors. Suffice to state a few facts. First, total private-sector employment in Texas in the third quarter of 2013 was 9,292,884, of which 298,535 was in Mining, Quarrying, and Oil and Gas Extraction (NAICS 21). The sector is one of the smaller in the state, making up only 3.2 pct of private employment. (For the record, public employment in Texas is roughly 1.5 million). Within NAICS 21, there are three main sub-sectors: Oil and Gas Extraction; Mining (except Oil and Gas); and, Support Activities for Mining. We are mainly concerned with the former, which I focus on from now on.

Second, the Oil and Gas sub-sector employed 107,664 in 2013Q3, representing about 36 pct of the sector. In turn, in that year, companies established 11 years ago (the oldest firms) or longer accounted for 82.5 pct of employment in the sub-sector, however that figure has been declining since 2009Q3, when it was over 86 pct. The largest companies (more than 5oo employees) in this sub-sector employed 70 pct of all workers as of 2013Q3, which is almost two percentage points lower than their share in 2009Q3. That is, both younger and smaller companies must be growing at a faster rate than larger and older companies. It is noteworthy, however, that the oldest companies employ more workers in the sector than do the largest companies; in order words many older companies remain relatively small. Two pie charts below summarize the distribution of employees according to firm age and firm size in Texas as of 2013Q3.

image (1) image (2)

The main take-way from the difference in composition of the sub-sector in terms of age and size of its firms is that this is not an entrepreneurial sector. Start-ups, which are typically younger firms, do not constitute a large portion of employment. This should come as no surprise for this highly capital-intensive industry. Start-ups (young firms) are generally supposed to be the great job-creators, on average, in the economy as a whole. Just over 10 pct of employment is at very small firms (those with fewer than 20 employees), which is less than the average in the Texan economy. As a point of reference, for all firms in Texas, almost 15 pct of employment is contained within this size tier of firms. Similarly, almost 50 pct of employment is contained at very large firms across all firms in Texas. Within Texas at least, the oil and gas sector stands out for the greater than average proportion of employment that is organized within the very largest companies.

Let’s look at the distribution of oil and gas employment in Texas at the county level. Below is a choropleth map of sub-sector employment as of the third quarter of 2013.


There are perhaps five main production areas for oil and gas in Texas. The largest would be metropolitan Houston, in the south east, on the Gulf Coast. Harris County, where downtown Houston is, appears to contain almost half of the sub-sector. This tells us that quite a bit of the sector is in office work, because I doubt there is much drilling or refining in downtown Houston. The rest of the sub-sector is mainly located in and around Dallas (Exxon, for example, has its corporate headquarters in a Dallas suburb, though most of the managerial, planning, and oversight work of the company happens in Houston) as well as way up in North Texas (Amarillo), in West Texas (Odessa), and finally in South Texas (Corpus Christi, San Antonio). Most of all that is likely hydraulic fracking operations.

Astute readers will notice I still haven’t actually talked about job creation in oil and gas in Texas yet. One of my larger points is to emphasize the context of job creation. To do that, we should be aware of the basic organizational structure and geography of the industry under examination. However, as is clear from the above discussion, there are multiple indicators that could legitimately be used to describe job creation. I use ‘firm job gains,’ which counts the gains in employment (between beginning and end of a quarter) at firms that grew over the quarter, and ‘firm job lesses,’ which counts the losses in employment at firms that shrank over the quarter. So the former indicator does not include instances where firms fired employees or employees retired if that firm was growing. That is, employment losses at expanding companies are not counted by this indicator. The opposite situation holds for ‘firm job gains.’ The point of these indicators is to isolate job creation (that is, the formation of new permanent positions in firms, or the liquidation of previously permanent positions) as opposed to employee turnover or replacement hiring. These indicators are explained in brief at the Quarterly Workforce Indicator download site operated by the US Census Bureau (http://ledextract.ces.census.gov/).

The graph below depicts the quarterly net change in jobs in the sub-sector for Texas as a whole from 2009 to 2013. This is job creation less destruction. Bear in mind that these statistics represent flows, not a stock like employment.

image (4)

There are some key points. First, job creation is mostly greatest during the second quarter of the year. This makes sense as layoffs typically happen around Christmas and the New Year, and hiring begins in earnest in January. Second, the volume of job creation increased by roughly 80 pct between 2010 and 2011 (second quarters of each year), and about 20 pct between 2011 and 2012 (second quarters). It declined by over 10 pct from 2012 to 2013. It appears that job creation in the sub-sector has slowed, but remains quite high. The main point here is that the sector really did not begin to deliver gains to employment until after 2010.

The map above has suggested that we should look at job creation in the industry as it happens in specific areas. Houston appears to be the center of the industry, so we should start there. Below, I’ve compiled the job creation and job destruction statistics for oil and gas extraction in Houston (metropolitan statistical area) as a share of Texas job creation and destruction in that sub-sector.

image (3)

An important pattern that could be observed with job creation figures is whether or not convergence/divergence is taking place between areas. That is, it may be the case that rising diseconomies of scale at firms co-located in an agglomeration (such as oil and gas companies in Houston) or perhaps more general urbanization diseconomies (Houston itself) are causing firms to downsize operations or even relocate to other areas (say, to refinery areas in Beaumont or Port Arthur or to commercial areas in Dallas). The above graphic suggests that, for the first three years of the economic recovery beginning in the autumn of 2009, the oil and gas sub-sector in Houston captured a greater share of job destruction than job creation. This is not to say that there was net job destruction in Houston; in only two quarters did destruction of jobs surpass the creation of jobs within oil and gas. Rather, the point is that there was some convergence happening as areas outside Houston bore relatively less of the job destruction. In other words, roughly half the consolidation in oil and gas employment in Texas happened in Houston. This is notable because less than half the job creation happened in Houston during that period, and as roughly half the sector is located Houston, there is some discrepancy here.

More importantly, this process didn’t hold up for very long. If during the first three years that this sector was creating jobs (and I am sure we could assume was mainly related to fracking) most of this activity was happening outside of the industry’s central area, then once 2012 rolled around, job creation shifted back towards Houston.

Driving the process of convergence/divergence may be the evolution and maturation of the industry. The oil and gas sector can be divided into two main types of operations: upstream and downstream. The former involves discovery and extraction, and the latter involves transportation and marketing. It is intuitive that in the early stages of an economic boom in the oil and gas sector (fracking), upstream activities would expand first. As those projects are completed and go online, the emphasis shifts towards managing the projects, which ostensibly requires less although more specialized labor, and which can be accomplished off-site. As such, upstream activities probably require co-location with accountants, project managers, budget analysts, etc. There is a clear spatial division implied in the industry and in a boom.

Bottom line

A plausible explanation, then, of why job creation in the sub-sector shifted is the basic maturation of the industry. Placing job creation in its spatial context, then, has raised some critical points about distributional fairness but also, I suggest, about the durability of job creation. Here are some concluding points.

First, ‘job creation’ is much more than a conversation about the source of job creation, whether demand from consumers (demand from business, incidentally, is an ignored factor, even though such demand drives a lot of activity in trade and professional services) or from the benevolence of oligarchs. I think that conversations about job creation are impoverished and boring as they are currently. The more interesting aspects, I argue, are the industrial organizational and geographical aspects. From this angle, we can approach the quality and location of job creation, which implies distributional; matters.

Second, the data we have available on job creation do not allow us to answer those conversations about causes of job creation. They do, however, allow us to examine questions of distributional fairness. For example, the above statistics have pointed out that Houston is a crucial area for the reproduction of this industry. Yet, there is clearly a change in how Houston benefits, and I interpret the statistics as indicating that Houston has more recently distributed job destruction away. This is part of a larger story about the durability of the fracking boom and how this boom distributes benefits and costs. The data raise questions about job creation that are not part of the conversation, but which can be used to trace its potential trajectories in the future.

Third, I am not optimistic about its future trajectories, at least from the perspective of non-core areas. There is obviously a spatial component to the specialization of the industry, and as the industry matures, on-site operations will be streamlined. There is more here than simply demand for oil and gas. This is truly a matter of project management, budgeting, and contracts between oil majors and specialized providers. Fracking projects have a life span on average of about seven years, and are most profitable typically in the first two or three years. As the demand for labor on-site wanes and as companies begin to scale down or possibly enter bankruptcy, we might need to expect some financial turmoil in these peripheral areas. There could be consolidation. There could be stresses in the local financial networks, such as banks that finance commercial and industrial loans. There may be pressure on local spending and municipal tax revenues. Job creation may actually be a leading indicator of economic prospects.

A next step might be to perform a cluster analysis that identifies and isolates areas of fracking production (county or metropolitan scale) and then determines the extent to which job creation was shared between them. The timing of such changes would also be an interesting point. The cases of oil and gas specifically and Texas more generally deserve greater attention because Texas has captured so much of the employment growth since the nominal end of the recession and the fracking boom has been critical to its success. It’s development will have an impact on the US as a whole and certainly Gulf Coast area. We need to pay attention to this, examine the context of job creation, identify its locational attributes, and then we can speculate on the prospects of job creation. In this context, the source of job creation is only one aspect among many. The real questions cannot necessarily be answered by the data we have available, yet they do raise a number of other illuminating questions.

Nonetheless, left/progressive commentators should really cut it out with their thoughtless statements about job creation. Learn about which sectors are creating jobs, where they are creating them, and consider the context of those industries (namely production processes relations with other sectors, etc), and then maybe the conversation will take off.

Employment update: the job creation meme

On the radio yesterday morning, some DJ quoted Hillary Clinton, who recently said that ‘business don’t create jobs’ or something along those lines. The statement is meant, I believe, to reflect the notion that consumers create jobs, through their demand for goods and services. Implicitly, the statement seeks to counter the argument that the governing plutocrats are benevolent and generous ‘job creators.’ I think it was a mistake for left/progressive commentators to adopt this theme, but it is here, so let’s first take a look at the process of job creation and then employment and job statistics. My question is: what do we know about job creation, conceptually and descriptively? The post here is going to tackle the first of these, and I’ll write-up another one with some data later.


First of all, businesses change the number of jobs recorded in the formal economy by adding workers to or removing them from their payrolls. We know that businesses ‘create jobs’ because the government counts jobs as the number of workers who are employed by firms. So, purely from a methodological perspective, when we talk about jobs, we are talking about the gains and losses of salaried/employed workers at US firms (and occasionally at government agencies) as reported by payroll data (which in turn are reported to the almighty IRS).

Second, businesses do not want to create jobs. Employees are costly, and employers are really only going to hire a new employee after other efforts to cope with increasing workloads (overtime, or productivity-enhancing strategies, for instance) have failed to relieve the stresses from the rising demand for their goods and services. Clearly, there is an important relationship between demand for a firm’s output and the way that the firm adjusts to this changing demand. It is not necessarily the case that a firm will hire more workers as demand rises. Some owners are incompetent, for example. Some firms enter into long-term contracts that so structure their budgets that they simply cannot hire new workers, while other contracts make firing difficult. There is also a tremendous amount of uncertainty in the economy. The process of hiring and firing may be responding to events that are not fully formed or are ambiguous. So when a firm decides to hire/fire an employee, the process will usually be undertaken in the face of exigent circumstances. Again, business don’t want to do this. It’s expensive, it’s uncertain whether it will solve its workload problems, and it may be based on faulty information about its business prospects.

Third, the hiring/firing process is one of the miracles of the economy. I use ‘miracles’ advisedly because it is, in fact, a process that is extraordinary, a welcome but surprising event, and difficult to be observed or explained. Job creation statistics do not actually observe the hiring and firing process. Remember that those statistics simply count the reported number of employed workers at firms at a given time (beginning or end of the quarter, usually). If you want to actually see the phenomena of job creation, you will need to be either a manager or a (prospective/former) employee. The Census doesn’t see job creation; I can’t see ‘job creation’ happening directly. This is partly semantics, but also it should emphasize the fact that the process is personal and sociological. That is, hiring/firing really comes down to a host of economic, political, and cultural factors that are probably highly specific to context (national, regional, sectoral), with a dose of randomness as well. My point here is, if you really want to understand job creation, then you should absolutely be talking to prospective employees, recently hired employees, recently fired employees, and the people who hire and fire them. Then you can get a sense of how the process works.

These are some preliminary comments. In a post later I will elaborate on how job creation happens between sectors and how it varies depending on the quantitative measures utilized.

The loan to deposit ratio and the trouble with US finance

 The three problems in US finance revisited

In an earlier post, I suggested there were three core problems with US finance: tendency towards dysfunction; uneven cost and access to financial services; and, waste, redundancy, and fraud. I was just browsing through blogs and saw a post at zerohedge (http://bit.ly/1so7Gd9). It is entitled ‘All that is broken with the US financial system in one chart’ and shows the loan to deposit ratio at JP Morgan from 2008 to now. The question I’m asking myself is: does JPM’s loan to deposit ratio really tell us everything wrong with US finance? Does it reveal the US tendency to undermine profitability and stability by way of incentives to misallocate credit? Does it reveal the uneven ability for consumers to access credit on good terms? Does it reveal the wastefulness of the US system, the high incidence of consumer fraud, and the high incidence of white-collar fraud?

The first thing I note is that I don’t think the 2008 to 2014 period is satisfactory for answering these questions. Furthermore, there is no comparison to other large banks, even though JPM on its own has market power and can be considered a special case worthy of analysis. I don’t post comments on that blog, but I did notice in the comments section someone asking if there was a chart for the whole financial system. The implicit criticism, I think, was that JPM is not indicative of the rest of the banking system, even though it is the largest bank in terms of deposits, or at least in the top four. I think a better starting point is asking whether or not the loan to deposit ratio can capture the problems in US finance, and then proceeding with individual banks to understand how the ratio is constructed organizationally and geographically.

I’ve attached below a chart created using FRED (http://research.stlouisfed.org/fred2/), showing the ratio of loans & leases to deposits at US commercial banks. It begins in 1973 and continues monthly to the start of October 2014.

Loan to deposit ratio, US commercial banks

It seems to me this is another important institutional relationship in US finance. Some notable features include: (1) the ratio currently stands at its lowest level since the late 1970s; (2) it peaked during the dot.com bubble, and even the mortgage lending boom could not raise the ratio to its previous peak (which suggests some interesting limits to leverage); (3) it increased rapidly starting in the mid-1990s economic boom; and, (4) it had been in decline from the panic in 2008 until earlier this year.

There are a number of different behaviors that affect the ratio. First is clearly the demand for credit, which is structured by access and cost. Demand, by this token, is affected by the organization of credit allocation, that is the specific institutions responsible for providing it (too-big-to-fail banks, savings associations, credit unions, payday lending). Second is the effect of interest rates, which affect willingness to take on risk by banks. Third is capital and other regulatory requirements.

So, does this institutional relationship reveal the problems in US finance? This question assumes that the three-problems are valid; they may not be, and this is a good exercise to work that issue out.

1. Tendency towards dysfunction

The ratio tends to drop around US recessions, but it is interesting to note that it did not drop as much during the S&L debacle. Leverage actually appears to have increased from 1985 onwards, even through 1987 when there was a sharp drop in profitability of US banks. Even during a banking crisis, leverage continued to grow. It did, however, respond dramatically to the latest recession and banking crisis, however it is hard to separate out those effects. Did leverage decline after 2008 because of demand or because of supply side factors? I don’t know. At the least, the ratio might anticipate collapses, in that periods of expansion in leverage are followed by contractions, which is to be expected based on periods of credit expansion.

2. Cost and access is uneven

In order for us to determine whether or not the ratio can reveal the problem of access, it would probably be best to disaggregate the ratio between types of organizations. First would be sector (commercial banks, savings associations, credit unions, non-regulated intermediaries); second would be size of organization; and third would be the region of operations. It would be great if there were data on the average ratio by banking markets served (which could then be related to other demographic features of those markets, such as income, population, etc), but that would be quite an undertaking. At least in general terms, the ratio suggests that there has been a significant pullback in leverage; as we cannot quantify the factors that contributed to that (it could be demand, regulation, and supply), it is difficult to know whether or not the pullback reflects lower willingness by consumers to take on debt or greater risk aversion by banks. The post at zerohedge argues that the flatlining in amount of loans outstanding indicates a conscious decision by the bank not to extend loans; I think we would need more data on the volume of loan applications as well as the rate at which applications are accepted. The Federal Reserve has survey data from banks, which speaks in a way to sentiment, but hard data would be more useful.

Another important point that comes to mind, and which returns to the issue of access and organization type, is that using commercial banks to determine lending might actually be misleading. As I’ve posted before, regulated banks are actually performing less lending. The ‘shadow’ financial sector has been encroaching on traditional lending markets for decades. It may be the case that the growth of shadow activities in financial markets has lowered the share of commercial banks in lending. To develop this line of inquiry further, one would need to explain that this pattern accelerated after 2008.

3. Waste and fraud

On the whole, the ratio really seems to be an indicator of system-wide leverage. It does not seem capable of tackling issues of consumer fraud, white-collar crime, etc.


I am weary of these reductionist articles that pop up on so many blogs and online news sites. The problems in the US financial system cannot be boiled down to any one factor. The sector is too heterogeneous for there to be even one set of factors. Clearly, there are more than three problems as well, but I’ve tried to make it so that other “sub-problems” can be filed under those categories. Again, the endeavor to determine just exactly what is wrong with US finance has to take place on a lot of levels–regional, sectoral, historical, institutional, etc. The key may be to generate case studies that are regionally and institutionally specific and see what kinds of patterns and differences can be identified. That said, I’m glad to add the ratio to the list of relevant institutions of finance.

Employment update: Texas employment growth

There is nothing I enjoy more than reading through spreadsheets of employment data. And I am certainly not being sarcastic here, this is the life of a nerd.

Part of the reason I enjoy reading through them so much is that when you deal with sector-level classification schemes (the North American Industrial Classification System, NAICS, is the one with which I have the most experience from my graduate work), you encounter some very funny occupations. They are funny, on one hand, because so many occupations are activities that you though were obsolete already, and there is something a little funny about the past (buggy-drivers, for instance, are a little funny; see what I mean?). On the other hand, they are funny in the way that bureaucracy is funny, like what you would read in Kafka or see in Terry Gilliam movie. Bureaucrats are uptight and fussy, which is pretty funny when you think about it; and you definitely get a sense of that fussiness reading through these spreadsheets.

As a short example, I’ve got in a figure below the ten industry sectors that grew the most in terms of employment in Texas from the third quarter of 2009 to the third quarter of 2013, and the ten sectors that contracted the most. This is mainly due to the influence of the book I am currently reading at the moment, Rough Country by R Wuthnow about the role of religion in Texas history. I am routinely sidetracked by my thoughts while reading, and this blog post follows one of the occasions.

Here are the largest contractions.

Contracting Industries NAICS Emp 2009 Emp 2013 Chg
Funds, Trusts, and Other Financial Vehicles 525 8356 78 -0.9906654
Electronics and Appliance Stores 443 38704 5352 -0.8617197
Rail Transportation 482 74 46 -0.3783784
Private Households 814 21290 16544 -0.2229216
Motion Picture and Sound Recording Industries 521 2026 1584 -0.2181639
Broadcasting (except Internet) 515 22571 18789 -0.1675601
Administration of Human Resource Programs 923 36668 32386 -0.1167776
Printing and Related Support Activities 323 29100 25732 -0.1157388
Apparel Manufacturing 315 4894 4370 -0.1070699
Publishing Industries (except Internet) 511 44231 40151 -0.092243

Some comments. I find it hard to believe the figures for 525; this must have something to do with counting error, which I’ve encountered a few times elsewhere in NAICS statistics. Second largest drop: electronics stores. That’s RadioShack, I guess. What’s incredible is the drop: from 38 thousand to five thousand! That is low-skilled service work after all, so ostensibly those workers can find jobs in other retail activities, although that isn’t much of a consolation. There are five thousand fewer people working in private households, so it seems that the wealthy have cut back on their excesses, out of solidarity with the working classes no doubt. Also four thousand cut from Administration of Human Resource Programs; so the rationalizers were rationalized. Printing also by four thousand. This classification is a little ironic; as printing of papers declines, printing of materials is growing (3-D), but it really seems to be evolving into just another large electronic item you would buy for your house, like a washing machine or entertainment system. Finally, Publishing Industries (except Internet) also declined by about four thousand. Several sectors include the “excluding the Internet” qualifier; economic history in the making.

Here are the largest positive employment changes.

Growth Industries NAICS Emp 2009 Emp 2013 Chg
Fabricated Metal Product Manufacturing 332 116206 138366 0.1906958
Oil and Gas Extraction 211 89965 107668 0.1967765
Securites, Commodity Contracts, and Other Financial Investmens and Related Activities 523 49272 62066 0.2596607
Machinery Manufacturing 333 86382 109960 0.2729504
Truck Transportation 484 104578 134310 0.2843045
Forestry and Logging 114 415 535 0.2891566
Wholesale Electronic Markets and Agents and Brokers 425 58507 75664 0.293247
Support Activities for Mining 213 100794 177155 0.7575947
Sporting Goods, Hobby, Book and Music Stores 451 39248 72612 0.8500815
Postal Service 491 325 856 1.633846

Some comments. These are mostly big industries. I notice that Texas has a lot of people in manufacturing (about 130 thousand in fabricated metal and another 100 thousand in metal machinery). It sure has an enormous pool of skilled labor, which is even more interesting in the context of it being a right-to-work state; how many of these workers are members of a union? What are their wages? What is the level of labor turnover? Oil and gas extraction as well as mining support together make up over another quarter of a million workers; all growing after crisis by significant amounts. Yet another very large sector with skilled and highly regulated/licensed labor is truck transportation; obviously on account of US trade with Mexico and the great amount of industrial production. The securities sector has also expanded by leaps and bounds, in the wake, oddly enough, of a major financial panic. I suspect mostly this labor is located in Dallas and perhaps Houston. Maybe this has something to do with fracking as well, as big oil is hugely preoccupied with risk management through financial markets. Fracking boom in Texas may translate into risk management boom as well. FInally, I am slightly relieved by the expansion in Sporting Goods, Hobby, Book, and Music Stores–hopefully the workers displaced from Electronic Goods Stores have found their way into these stores, which hopefully will enjoy a long life. Unless Amazon wipes them out first.

In short, quite a story of economic success. These figures give an interesting insight into why Texas has prospered after the crash. That story still needs to be developed.

I place a lot of value in government statistics like employment figures because as an undergraduate, I majored in Near Eastern archaeology. Being able to read into the lives of past civilizations is so worthwhile; you get such a sense of that when you have an idea as to what people were doing and how they were organized. It’s hard to make historical employment and economic figures interesting, but economic history is fascinating.