tag:blogger.com,1999:blog-52875272369414824152024-03-18T20:27:42.271-07:00John HandleyJohn Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.comBlogger13125tag:blogger.com,1999:blog-5287527236941482415.post-44226703690915988292017-11-18T03:29:00.002-08:002017-11-18T03:29:25.635-08:00Convergence Conditional On What?<div dir="ltr" style="text-align: left;" trbidi="on">
About two months ago, I wrote a <a href="https://jwhandley.blogspot.com/2017/09/the-g7-productivity-puzzle.html">post</a> about the weird lack of economic convergence in the G7 -- Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States. Neoclassical growth theory suggests that countries with similar economic institutions, levels of investment, and population growth (e.g., the G7) should all converge to similar levels of labor productivity. The fact that this doesn't happen, or has stopped happening for different countries at different times (Canada in the 1980s, Japan and Italy in the 1990s, the UK since 2010), flies in the face of the 'absolute convergence' hypothesis.<br />
<br />
Unlike the evidence against absolute convergence from other countries, however, members of the G7 haven't been diverging from each other in terms of GDP per capita over the last few decades, per se. Instead, there seems to be something affecting the <i>level</i> of each countries productivity over time. In terms of GDP per hour worked, the UK is consistently around 75% as productive as the US, Japan is about 65% as productive, and Germany and France roughly match the US. The Solow model does have predict some variability in productivity levels based on the savings rate, the population growth rate, and depreciation. However, all of these differences should be controlled for if you look at total factor of productivity, which is what I tried to do in my previous post. Long story short, the Solow model fails almost entirely in explaining productivity differences across the G7.<br />
<br />
Economists from the '90s are probably screaming right now that I should look at <a href="https://eml.berkeley.edu/~dromer/papers/MRW_QJE1992.pdf">human capital</a> and test for convergence <i>conditional</i> on that. My issue with looking at human capital is that 1) nobody even knows <a href="http://worthwhile.typepad.com/worthwhile_canadian_initi/2015/02/human-capital-and-land-capital.html">what it is</a> and 2) the way it's used in theories is really strange. For instance, in the paper I linked above, Mankiw et al famously model human capital as just another kind of capital in a Cobb-Douglas production function and then assert that it accumulates in the same way are normal capital, i.e. through saving/investment. They then assert that the savings rate for human capital is equal to the share of the working age population that is in school (even though in their model human capital investment is a portion of income).<br />
<br />
Still, the idea of conditional convergence is intriguing, so why not regress growth from 1981 to 2015 on the initial level of productivity and some crude measure of human capital (percentage of population with a post-secondary degree)? For the heck of it, let's throw in R&D spending as a percentage of GDP.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQpI6IXqREr3O0k3KHKtR6yuiAdeplO1RUwvnmd7TlnuxMhT_4idHpu2Nwga2T-IUIW3rDCLe1i8YLlwDJwiH4Z_4zvBAaXAH5l_RGzT0iTjaQJuUZLY46EdLpv5ALpFctA9oY2JxFKo-H/s1600/Conditional+Convergence.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="461" data-original-width="460" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhQpI6IXqREr3O0k3KHKtR6yuiAdeplO1RUwvnmd7TlnuxMhT_4idHpu2Nwga2T-IUIW3rDCLe1i8YLlwDJwiH4Z_4zvBAaXAH5l_RGzT0iTjaQJuUZLY46EdLpv5ALpFctA9oY2JxFKo-H/s320/Conditional+Convergence.png" width="319" /></a></div>
Interestingly enough, the fit is actually astonishingly good, especially considering that I only used data from seven countries. I was also surprised to see that the (statistically insignificant) coefficient on tertiary degree attainment is negative. There's probably a better measure of 'human capital', but I still think there's something strange about using anything as a proxy for an inherently unmeasurable theoretical construct.<br />
<br />
If you exclude the education variable, then the results are as follows:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhs2-KYix08vv-dkhXPGgWDoci64LBX3qnMVMNBk9_bmXCVwzSXPpe1ynore3_Xe0czrvzXTaHodsxoU9R0Dz0o8JPdceRvzvI-ISxvOl6RXWj7eicpbjdWRUrohQv7Gdvu4FfmoGD7IBx6/s1600/Conditional+Convergence+-+no+hc.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="429" data-original-width="457" height="300" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhs2-KYix08vv-dkhXPGgWDoci64LBX3qnMVMNBk9_bmXCVwzSXPpe1ynore3_Xe0czrvzXTaHodsxoU9R0Dz0o8JPdceRvzvI-ISxvOl6RXWj7eicpbjdWRUrohQv7Gdvu4FfmoGD7IBx6/s320/Conditional+Convergence+-+no+hc.png" width="320" /></a></div>
The coefficient of R&D spending does change, but the main result here is consistent: strong support for the hypothesis that productivity in the G7 converges <i>conditional on R&D spending</i>. The equation that I tested was<br />
<br />
growth from 1981 to 2015 = a * GDP per hour in 2015 + b * average R&D spending from 1981 to 2015 + c<br />
<br />
All values are relative to the US, so you can predict the relative level of GDP per hour in the long run by plugging in a value R&D spending and then solving for GDP per hour. Assuming a level of R&D spending equal to the US, the regression predicts complete convergence: 43.1548/0.4155 ≈ 104% of US productivity.<br />
<br />
Alternatively, you can compare actual productivity in 2015 to productivity predicted by the model and a counterfactual with R&D spending equal to the US:<br />
<br />
<table>
<tbody>
<tr>
<th>Country</th>
<th>Productivity</th>
<th>Prediction</th>
<th>Counterfactual</th>
</tr>
<tr>
<td>Canada</td>
<td>76.915034</td>
<td>81.727441</td>
<td>94.292790</td>
</tr>
<tr>
<td>France</td>
<td>94.021332</td>
<td>89.476058</td>
<td>95.644441</td>
</tr>
<tr>
<td>Germany</td>
<td>93.728856</td>
<td>93.321678</td>
<td>94.395491</td>
</tr>
<tr>
<td>Italy</td>
<td>75.604129</td>
<td>75.233253</td>
<td>96.770322</td>
</tr>
<tr>
<td>Japan</td>
<td>65.538401</td>
<td>66.124831</td>
<td>63.949169</td>
</tr>
<tr>
<td>United Kingdom</td>
<td>75.644250</td>
<td>73.969879</td>
<td>83.190180</td>
</tr>
<tr>
<td>United States</td>
<td>100.000000</td>
<td>101.604800</td>
<td>101.604800</td>
</tr>
</tbody></table>
<br />
This approach predicts actual productivity levels surprisingly well (removing R&D spending from the regression reduces the r-squared value to 0.522). It also seems to suggest that Japan's low productivity levels should be of no surprise; it just started from such a low level that we should expect it to take a while longer to converge completely. Similarly, Canada, Italy, and the UK look to be suffering simply from low R&D spending.<br />
<br />
Even though R&D does appear to explain productivity differences in the G7, I am hesitant to say I've solved my puzzle yet. Looking specifically at Japan, it's period of high growth occurred when R&D spending was low, and subsequently higher R&D spending has coincided with lower growth. Another problem is the tiny sample size. Seven countries is far too small to make any serious conclusions (if I calculated correctly, the standard deviation on the estimate for the amount of convergence in the long run is 35.2). So I end this post barely more sure of what causes productivity differences between developed countries than I was two months ago, but maybe a slightly better idea of where to go from here.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-40347746453847253712017-10-19T05:58:00.000-07:002017-10-19T22:39:39.101-07:00Are there scientific facts?<div dir="ltr" style="text-align: left;" trbidi="on">
The response to <a href="https://twitter.com/Alec_Ksiazek/status/918511763326406657">this tweet</a> has been so large that it even touched my economics-packed Twitter feed (via Noah Smith). Noah has a relatively reasonable <a href="https://twitter.com/Noahpinion/status/920042058982838274">response</a> to the idea that "scientific facts are social constructs," although I am still annoyed about his misguided use of the word "anti-<a href="https://en.wikipedia.org/wiki/Rationalism">rationalism</a>" to describe anti-intellectual or anti-science arguments.<br />
<br />
Noah's ignorance of philosophy is fitting, because I (unlike Jason Smith, who called the ensuing argument an "<a href="http://informationtransfereconomics.blogspot.jp/2017/10/social-constructs-are-social-constructs.html">utter philosophical mess</a>") think that most people have failed to understand that this argument is really all about philosophy; specifically, philosophy of science. I think both Jason (and somewhat Noah) focused too much on the word "social" and too little on what "social" and "constructs" mean together -- namely that scientific facts (which are really theories or their predictions) are socially constructed and therefore do not refer to things in the real world.<br />
<br />
This is scientific anti-realism, or the idea that scientific theories don't or can't interact with reality. It's probably better to look at anti-realism through the lens of <a href="https://plato.stanford.edu/entries/scientific-realism/">scientific realism</a>. A scientific realist would say that scientific theories are either true or will eventually converge to truth given enough time and resources. Anti-realists are skeptical of the truth of scientific facts for various reasons -- for instance, the anthropology professor would probably say that society influences the scientific process such that the results it achieves are not true. Thomas Kuhn (or at least many readers of <i>The Structure of Scientific Revolutions</i>) would argue that "scientific facts" are inherently influenced by the prevailing paradigm.<br />
<br />
The folly of scientists in this case has been to unwittingly invoke their realism in attempts to mock anti-realists. Neil deGrasse Tyson's tweet was particularly ironic:<br />
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Dr. Tyson argued against the mere assertion of scientific anti-realism by asserting his own philosophical position (without making any arguments for it, I might add).<br />
<br />
Jason concedes that scientific facts in the past have been social constructs:<br />
<blockquote class="tr_bq">
One of my [favorite examples] is the aether. That was a "scientific fact" that was
a "social construct": humans thought "waves" traveled in "a medium",
and therefore needed a medium for light waves to travel in. This turned
out to be unnecessary, and it is possible that someone reading a power
point slide that said "scientific facts are social constructs" might
have gotten from the aether to special relativity a bit faster.</blockquote>
Another example is the geocentric model of the solar system, which is relatively empirically accurate yet no longer accepted as an explanation for planetary movements. The anti-realist argument is simply that there is no reason to believe we are completely right <i>this time</i>, let alone that we will eventually be right about everything.<br />
<br />
The problem with Jason's blog post is that he did precious little to defend his scientific realism before asking if we can "get away from the philosophical argy bargy." As the only economics blogger I can remember referring to Popperian falsificationism, I am more than a little bit disappointed (and frankly annoyed) at his dismissal of the philosophical argument here.<br />
<br />
Personally, I don't even agree with "scientific facts are social constructs." I just hate the arrogance of people in their ignorance. There are better arguments for why science is worthwhile, and reasonably objective than just assuming that to be the case. My favorite is pragmatism (which should appeal to the effective-theory-espousing Jason Smith), which basically sees the empirical successes of science as reasons for us to act <i>as if</i> scientific realism is true.<br />
<br />
I think Pierce's formulation of truth, while being as far from succinct as it is possible to be, is a good description of a pragmatic view of science:<br />
<blockquote class="tr_bq">
Truth is that concordance of an abstract statement with the ideal limit
towards which endless investigation would tend to bring scientific
belief, which concordance the abstract statement may possess by virtue
of the confession of its inaccuracy and one-sidedness, and this
confession is an essential ingredient of truth.</blockquote>
Basically, truth (in the pragmatic sense) is what science would come up with given infinite resources and infinite time.<br />
<br />
Honestly, though, any defense of scientific realism (even Noah Smith's argument that anti-realism is counterproductive because it fosters anti-rationalism -- more accurately anti-scientific beliefs) is better than "but scientific facts exist because we have smart phones."</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-21061756345538735872017-09-19T23:49:00.000-07:002017-09-20T03:02:28.614-07:00Economic Growth is All About Increasing Returns to Scale<div dir="ltr" style="text-align: left;" trbidi="on">
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<br />
<br />
Jason Smith has written a <a href="http://informationtransfereconomics.blogspot.jp/2017/09/information-real-nominal-and-solow.html">response</a> to my previous <a href="https://jwhandley.blogspot.com/2017/09/the-g7-productivity-puzzle.html">post</a> in which he brings up a few interesting criticisms of growth economics. Namely, he questions the attachment to constant returns to scale in the Solow model, which made me realize (or at least clarified my thinking about the fact that) growth theory is really all about increasing returns to scale.<br />
<br />
<br />
The original aim of neoclassical growth theory was to provide a rudimentary explanation for why some countries are poorer than other, or really why some countries produce less output per capita than others. Income differences can be explained by 1) differences in the skills of workers in each country and 2) differences in the amount of capital per worker (or per hour worked).<br />
<br />
This is because the factors of production (ignoring land) are generally considered to be capital (e.g. tools, machines, or computers) and labor, but the conventional theory of production presents a problem: economists like to assume constant returns to scale so that doubling the factors of production will double output. As Smith admits in his post, this intuitively makes sense, at least when dealing with real quantities:<br />
<blockquote class="tr_bq">
Constant returns to scale is frequently justified by ‘replication arguments’: if you double the factory machines (capital) and the people working them (labor), you double output. Already there's a bit of a 19th century mindset going in here: constant returns to scale might be true to a decent approximation for drilling holes in pieces of wood with drill presses.</blockquote>
The problem with this formulation is that economic growth with constant returns to scale is impossible because you can never increase output by more than the amount of increase in inputs. More specifically, if you adopt a production function with constant returns to scale, e.g. Solow’s $Y = K^\alpha L^{1-\alpha}$, then<br />
$$\frac{dY}{Y} = \frac{\partial K}{\partial Y}\frac{dK}{Y} + \frac{\partial L}{\partial Y}\frac{dL}{Y}$$<br />
Which is<br />
$$\frac{dY}{Y} = \alpha \frac{dK}{K} + (1-\alpha)\frac{dL}{L}$$<br />
Since $0 < \alpha < 1$ by assumption, growth in output ($\frac{dY}{Y}$) will always be less than the growth in capital or labor. This means that the only two ways to have exponential growth with constant returns to scale are 1) have labor grow forever (resulting in infinitesimal output per capita) and 2) have capital grow forever (resulting in an infinite capital to income ratio).<br />
<br />
Obviously the first option is inconsistent with exponential growth in GDP per capita, so we can reject it immediately as an explanation for economic growth while the second option implies infinite capital accumulation, which won’t happen because (since capital depreciates over time) that would imply an increasing share of income going to savings over time.<br />
<br />
The solution to this problem is to add some mechanism for increasing returns to scale. The Solow model leaves this process implicit — much to Smith’s chagrin — by calling it technological progress and assuming constant growth but the rest of growth theory is just attempts to augment production to allow for increasing returns to scale.<br />
<br />
The simplest way of doing this, which is similar to what Smith does near the end of his post, is to assume that Solow’s Total Factor of Productivity is just some function of capital and labor. This is the logic behind the AK model, which takes the neoclassical production function $Y = BK^\alpha L^{1-\alpha}$ and assumes $B = AK^{1-\alpha}L^{\alpha-1}$. Plugging $B$ in results in<br />
$$Y = AK$$<br />
Other models are more sophisticated; they try to add things like <a href="https://eml.berkeley.edu/~dromer/papers/MRW_QJE1992.pdf">human capital</a> or <a href="http://lhendricks.org/econ520/growth/RandD_SL.pdf">research and development</a>. But the underlying principle remains the same: growth theory is basically about finding ways to justify increasing returns to scale. Smith’s approach (ignoring his focus on nominal values) is just a much more explicit way of adding increasing returns to models. In this sense, Smith is right that the original assumption of constant returns to scale “leads to the invention of "total factor productivity" to account for the fact that the straitjacket we applied to the production function (for the purpose of explaining growth, by the way) makes it unable to explain growth.” The real difference is that economists want to model the underlying process that allows for increasing returns while Jason is content with allowing increasing returns to scale from the get go.<br />
<br />
<br />
Update: I know the AK model is really just constant returns to scale for capital, but the real point is that, for sustained economic growth, there cannot be decreasing returns to scale for a non-labor factor of production. Otherwise, output per worker can't increase along a balanced growth path (which is when the other factor(s) of production don't grow faster or slower than output in the long run). </div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-11677152463469642492017-09-19T04:54:00.004-07:002017-09-19T04:55:28.889-07:00The G7 Productivity Puzzle<div dir="ltr" style="text-align: left;" trbidi="on">
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With the exception of the US (and maybe Canada and Germany), all of the countries in the G7 have pretty <a href="https://data.worldbank.org/share/widget?indicators=NY.GDP.PCAP.PP.KD&locations=GB-JP-DE-US-FR-CA-IT">similar levels of GDP per capita</a>. In constant price PPP terms, Japan, France, and the UK are all around 38,000 USD, while Italy is a bit lower at 34,000 USD (the Great Recession really hurt Italy, which has also been in a long term decline for a couple decades), and Germany and Canada are both about 44,000 USD.<br />
<br />
This clustering in GDP per capita strikes me as a little bit strange, since employment-population ratios and average hours per employee vary drastically across countries. People in France work a lot fewer hours than their neighbors across the English channel for the same amount of output, while people in Japan work infamously long hours and seemingly get nothing out of it.<br />
<br />
I guess I would expect labor productivity (<a href="https://data.oecd.org/chart/4W8Y">GDP per hour worked</a>) to be differ between countries a little bit, but it seems strange to me that unconditional convergence hasn't even held between western democracies. America seems to have some magical ability to be more productive than every country but France and Germany, and the UK is inexplicably much poorer than its European neighbors. Italy has understandably been a mess since the days of Silvio Berlusconi, but Japan's perennially low productivity does not match its reputation as a paragon of efficiency.<br />
<br />
I also tried adjusting for the size of the capital stock in each country, with little success. First, I assumed output in each country of the G7 is produced with a typical neoclassical/Cobb-Douglas production function, i.e.<br />
$$Y_t = A_t K_t^\alpha H_t^{1-\alpha}$$<br />
where $Y_t$ is GDP, $A_t$ is total factor of productivity (TFP), $K_t$ is capital, and $H_t$ is total hours worked. Working with the somewhat unrealistic assumption that $\alpha$ (capital's share of output) is constant at $0.34$ for all of the G7, I calculated TFP by dividing $Y_t$ by $K_t^\alpha H_t^{1-\alpha}$[1]:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgcuKZrVycxwPApaazpY0ba_E7c7BVsGuPP64bKalV_bSMwmJvws424SjFwEUqAVjzSOE7Cg4p-ulxlBDlThgoS80OK1UAehUrhgIt2MfzfwkBLMgH8cZh0hN2eK6gLmWwI3GdpYvH1dKYn/s1600/G7+TFP.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgcuKZrVycxwPApaazpY0ba_E7c7BVsGuPP64bKalV_bSMwmJvws424SjFwEUqAVjzSOE7Cg4p-ulxlBDlThgoS80OK1UAehUrhgIt2MfzfwkBLMgH8cZh0hN2eK6gLmWwI3GdpYvH1dKYn/s400/G7+TFP.png" width="400" /></a></div>
I didn't include Germany or Italy in the chart because they are mostly similar to France (Italy started falling to the level of the UK and Japan in the mid-nineties, though) and they crowded out the more interesting information. Looking at TFP instead of hourly output presents about as many questions as it answers. First, it becomes clear that Canada, France, and Germany are equally as productive, but that Canada and Germany do a much better job of ensuring full employment than France does (this isn't just a difference in hours either, Germans work fewer hours per year than French people). But why did Canada slow down relative to the US in the eighties? And what the heck is going on with Japan here?<br />
<br />
My partiality to the UK makes me happy that at least Britain is better off than Japan (incidentally my second favorite country in the G7), but I'm a little bit skeptical that even two world wars and decolonization made the UK lose 40% of its productive capacity relative to the United States, especially when the end of French empire didn't have the same consequences. Also, everyone talks about Japan's lost decade starting with the recession in the late 1990s, but the decline seems to have actually begun in the seventies, and the cause completely evades me.<br />
<br />
Whenever I read about growth/development economics, it's usually taken for granted that America is at the technological frontier and that explains its unusually high productivity, but Canada's relative smallness looks like the only thing that could prevent us from giving it that title, at least from 1950 to 1980.<br />
<br />
Unfortunately most of the growth/development economics research I encounter doesn't really care about 30% gaps between rich countries, but instead (and probably rightfully so) focuses on the 90% gaps between rich countries and poor ones -- heck, I'm looking into those gaps in Vietnam, Cambodia, Laos, and China for my school's version of a senior thesis. Maybe there is no real good explanation for why Japan or Britain haven't converged to America's level of GDP per capita in the 70 years since World War II, or why Canada has been losing ground for the last 30 years. It just really, really bothers me that there isn't.<br />
<br />
<br />
[1] All the data I used comes from the Penn World Tables. Capital is the capital stock at constant national prices, GDP is GDP at constant national prices (I would use PPPs, but capital is only available at constant national prices and current PPPs, and the data seem to match World Bank's idea of constant PPPs in that they are at PPP for the base year), and Hours is the product of average hours worked per person engaged and total persons engaged.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com3tag:blogger.com,1999:blog-5287527236941482415.post-25028494242672295272017-09-05T01:22:00.000-07:002017-09-05T17:20:44.306-07:00Econ 101 should at least do math right<div dir="ltr" style="text-align: left;" trbidi="on">
<div style="text-align: left;">
This is a small break from my normal type of post, but I've become a TA for my school's AP economics (AP = <a href="https://en.wikipedia.org/wiki/Advanced_Placement">Advanced Placement</a>, for those unfamiliar with the American and Canadian education systems) course, which has left me with a couple of takeaways:</div>
<ol style="text-align: left;">
<li>Calculus should be a prerequisite for economics</li>
<li>AP Econ/Econ 101 resorts to a lot of inconsistent nonsense in order to explain things to people who don't understand calculus</li>
</ol>
<div style="text-align: left;">
To remedy my annoyance at introductory economics (which I have confirmed from friends taking the same course at other schools universally explains the demand curve differently from the way it should/the way that is mathematically consistent with the rest of Econ 101), I decided to write down a derivation of the Econ 101 demand and supply curves in consistent way.</div>
<div style="text-align: left;">
<br /></div>
<div style="text-align: left;">
Under normal circumstances, I would probably rather criticize the theory for being unrealistic, but being clear about the math going on behind the scenes is all I choose to care about for the moment.</div>
<div style="text-align: left;">
<br /></div>
<div style="text-align: left;">
I should preface the math with an explanation of the way Econ 101 usually deals with the demand curve:</div>
<div style="text-align: left;">
There are a lot of people who come to a market that sells one item. Each person is willing to buy the item at any price lower than some arbitrary price, so if the owner of the market comes out and declares a high price, relatively few people will buy the item. Similarly, if the owner declares a low price, many people will buy it.</div>
<div style="text-align: left;">
<br /></div>
<div style="text-align: left;">
This explanation results in a weird demand curve with 'steps' at different prices whose width is determined by the number of people with their maximum price at that level. This is entirely different from the smooth curves instructors like to draw to illustrate demand, and inconsistent with the math used when teaching firm behavior (marginal revenue doesn't make sense when the demand curve is a bunch of steps).</div>
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<br /></div>
<div style="text-align: left;">
Anyway, this is how Econ 101 students (with at least an understanding of derivatives) should be taught supply and demand:</div>
<div style="text-align: left;">
<br /></div>
<div style="text-align: left;">
Demand Curve Derivation<br />
<br />
Consumers derive a certain amount of utility when they buy units of the good. This utility can be expressed as the function U(Q) where U stands for utility and Q is the quantity of the good that consumers purchase.<br />
<br />
Consumers pay the same price for each unit of the good that they buy, so their total cost is PQ where P is the price of the good.<br />
<br />
People want to maximize the net benefit they derive from buying units of the good. Mathematically this means maximizing U(Q) - PQ.<br />
<br />
We know from calculus that setting the derivative to zero will give us the maximum, so the net benefit maximizing quantity satisfies<br />
<br />
U'(Q) - P = 0 or U'(Q) = P<br />
<br />
This is the demand curve. The reason it is downward sloping is because of diminishing marginal utility -- the notion that each additional unit of the good is less valuable than the last. This means that U'(Q) is a negative function of Q, necessitating a downward sloping demand curve.<br />
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Supply Curve Derivation:<br />
<br />
Firms want to maximize profits, which are defined at their total revenue (PQ) minus total costs (C(Q)). They do this given what they know about the demand for their product, so they replace the P in PQ with U'(Q) from the demand curve. Thus, firms maximize<br />
<br />
U'(Q)Q - C(Q)<br />
<br />
meaning that<br />
<br />
d/dQ U'(Q)Q - C'(Q) = 0<br />
which is the same as<br />
U''(Q)Q + U'(Q) - C'(Q) = 0<br />
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The supply curve needs to be written as a function of P, so we can just substitute P in for U'(Q) above, yielding<br />
<br />
P = C'(Q) - U''(Q)Q<br />
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This is the supply curve.<br />
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Let's derive the demand and supply curves given example utility and cost functions:<br />
<br />
U(Q) = aln(Q)<br />
<br />
C(Q) = 1/3(Q-b)^3 - cQ^2 + dQ<br />
<br />
In this case, the demand curve should be<br />
P = U'(Q) = a/Q<br />
and the supply curve should be<br />
P = C'(Q) - U''(Q)Q = (Q-b)^2 - 2cQ + d + a/Q<br />
<br />
This example gives fancy curves similar to those you might draw as examples, but a simpler example does a better job of showing the types of the linear curves you might see in econ 101/AP Micro<br />
<br />
U(Q) = Qa - 0.5bQ^2<br />
<br />
C(Q) = Q^2 + cQ<br />
<br />
This gives the demand curve<br />
P = a - bQ<br />
and the supply curve<br />
P = 2Q + c - bQ = (2-b)Q + c </div>
</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com4tag:blogger.com,1999:blog-5287527236941482415.post-37292126166531136042017-08-25T04:58:00.002-07:002017-08-25T04:58:17.532-07:00Automation and Job Loss<div dir="ltr" style="text-align: left;" trbidi="on">
The prospect of automation, or more generally huge productivity improvements in different sectors of the economy, has a lot of people worried that millions of people will lose their jobs over the course of the next century. What will all the taxi drivers do, the reasoning goes, when driver-less cars are perfected? Alternatively, what happens to all the manufacturing workers when automation makes their jobs obsolete?<br />
<br />
This line of thinking has a serious problem: it assumes that aggregate demand for goods and services remains constant in the face of productivity improvements. Normally this won't be the case, because people generally want more, or at least better, stuff. If productivity improvements mean that society can now produce a 4k TV with half the amount of labor as it could two years ago, people will probably start buying more 4k TV's. Of course, some goods are inferior goods (people buy less of them as their incomes increase), but in aggregate Say's Law -- that supply creates its own demand -- seems to ring true, at least in the long run.<br />
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Maybe, at some point in the future, economy-wide productivity will be so high that people consciously choose to work fewer hours, or some parents will choose to stay at home instead of work full-time, but this would be nothing to worry about. In this case, lower employment is just the consequence of people acting in their best interests. With much higher wages, people can afford to spend more time doing leisurely activities, which they very well might prefer to more income.<br />
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Fear about automation is not entirely unfounded, though. In many industries, such as manufacturing, demand really does reach a ceiling -- each person only wants to buy so many refrigerators, for instance. This is part of the reason that manufacturing employment has fallen from over 17 million in 2000 to about 12 million last year. At some point, demand for certain goods and services stops growing with income.<br />
<br />
People who formerly had well-paying manufacturing jobs might be forced to take a low-paying service sector job, meaning that they will end up with a real pay cut while most consumers reap the benefits of cheaper manufactured goods. At this point, though, the problem is no longer about people losing jobs; it's about distribution of income. Policies that increase incomes for people who work in the service sector -- whether they take the form of direct transfers, minimum wage increases, or something else -- would go a long way toward solving the problem posed by technological enhancements or productivity growth.<br />
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Needless to say, at least for the foreseeable future, automation need not necessarily be that big of a concern. We shouldn't worry about millions of people losing their jobs; they will probably find work elsewhere. Instead, we need to make sure that no one is left behind as we steadily proceed toward a world without scarcity.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-31110065520964321312017-07-23T17:50:00.000-07:002017-07-23T18:01:01.675-07:00The Price of Health Care<div dir="ltr" style="text-align: left;" trbidi="on">
Even if you are only a little bit familiar with different health care systems in the world, you probably know that America spends more on health than any other country in the OECD in terms of both per capita and percentage of GDP. With such high spending, you would expect outcomes -- such as life expectancy or amenable mortality (basically preventable deaths) -- to be much better than other countries that spend less. Strangely, as data from a <a href="http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)31280-1/fulltext">recent paper</a> on the German health care system shows, this is not the case.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhPFsjLVvUsT3cZr0BC4Tg05rlvSKUANSvw0HBID-ij8ekH9h5QFp1XOT2X9XEG6F8Ei8OoXwIiBsf-BNSc4uXaMwByMuidj_Ye0aaf7FylFUrHiRbCdAvPd83QbQWV2R6zYPH3yYq1vyZf/s1600/Amenable+Mortality+Rate+in+selected+countries.jpg" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="561" data-original-width="941" height="237" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhPFsjLVvUsT3cZr0BC4Tg05rlvSKUANSvw0HBID-ij8ekH9h5QFp1XOT2X9XEG6F8Ei8OoXwIiBsf-BNSc4uXaMwByMuidj_Ye0aaf7FylFUrHiRbCdAvPd83QbQWV2R6zYPH3yYq1vyZf/s400/Amenable+Mortality+Rate+in+selected+countries.jpg" width="400" /></a></div>
In spite of massive spending increases and a relatively high baseline in 2000, the US remains significantly behind other developed countries in terms of preventable deaths. On top of this, the improvement in amenable mortality for each dollar of new spending is a lot lower than the other countries.<br />
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This is where <a href="https://stats.oecd.org/glossary/detail.asp?ID=2205">purchasing power parities</a> (PPPs) come in. High prices for various health care related goods and services such as prescription medication or MRI scans could explain much of America's elevated health care costs, rather than high quantity/quality of care. If this were the case, that would explain why American health care spending continues to rise rapidly without significant improvement in outcomes.<br />
<br />
Finding PPP data for different countries would shed light on this because it would give us a good comparison of the quantity of health care that each country consumes as opposed to the amount of money it spends. If the quantity of health care per capita in the US was similar to or less than other countries, then that would explain the lackluster outcomes it experiences.<br />
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Until recently there was no data that I could find for health care specific PPPs outside of Europe, but apparently in May the OECD and Eurostat published <a href="http://www.oecd.org/health/health-systems/International-Comparisons-of-Health-Prices-and-Volumes-New-Findings.pdf">a report</a> that updated the previous estimates with data from the US and a few other non-European countries. Figure 4 in the report shows that higher prices explain some, but by no means most of all, of the discrepancy between outcomes and spending in the US health care system.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhM_zDB4fJX6np7gLiAaScdlhyw5gnkpH9J_L2FfsRNZu2HC9uq-VQ5zBwDW10CYrrA_V5A-1jB-eAq88dUAPgK_JYHFXI70PiWd62z1z1O5_clubbiKb4qbOyrrkszdjfS_RHR8kwDBJ25/s1600/Health+PPP+Comparison.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="616" data-original-width="491" height="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhM_zDB4fJX6np7gLiAaScdlhyw5gnkpH9J_L2FfsRNZu2HC9uq-VQ5zBwDW10CYrrA_V5A-1jB-eAq88dUAPgK_JYHFXI70PiWd62z1z1O5_clubbiKb4qbOyrrkszdjfS_RHR8kwDBJ25/s400/Health+PPP+Comparison.png" width="318" /></a></div>
Alternative explanations as to why quality of health care lags spending so much in the US are necessary. Wasteful spending brought on by the gratuitous use of expensive tests and procedures and drugs probably makes a big difference here. Also, if there was a single payer insurance market, the government would have a significant amount of leverage in lowering prices, but it's unclear how much can be gained from fixing incentives and switching to single payer.<br />
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Health care spending in America is also <a href="https://ourworldindata.org/financing-healthcare/#what-was-the-consequence-of-growing-expenditure-without-insurance-expansion-in-the-us">highly concentrated</a> among high spenders, suggesting that programs that increase spending on people who currently don't have insurance (and therefore don't spend much right now) won't necessary do much to solve the problem. Reducing total spending might require curtailing superfluous spending on things like cosmetic surgery and rationing expensive procedures that many people depend on.<br />
<br />
Ultimately, the US has a lot to gain from health care reform that increases coverage and -- hopefully -- reduces costs, but we should all be wary of thinking we can get a free lunch on health care.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-49663383802257962452017-07-14T17:02:00.001-07:002017-07-14T17:02:17.208-07:00East Asia and Economic Convergence<div dir="ltr" style="text-align: left;" trbidi="on">
Japan's impressive post-WWII economic growth is a prime example of economic convergence -- Japan's GDP per capita went from a little under 40% of the US in 1960 to over 90% in the early 1990s. This is a classic prediction of the <a href="https://en.wikipedia.org/wiki/Solow%E2%80%93Swan_model">Solow growth model</a>; poorer countries will have quick economic growth as they invest in capital and will slowly catch up to rich countries like the United States.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirsJBCRTa-R0VPoCea1VXpSmJ3w6ueiF7Zv5KzjBOoirOdicUZDVLSWk3-XMxcaC_zHE30vITa0gIWIYSp9CPTYQQBvDPMSGh8DSvdmQ07UJp0nv7dMDCiEPcbU0chy4eDruSrYrXt2wrm/s1600/Japan-US+GDP+per+capita.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirsJBCRTa-R0VPoCea1VXpSmJ3w6ueiF7Zv5KzjBOoirOdicUZDVLSWk3-XMxcaC_zHE30vITa0gIWIYSp9CPTYQQBvDPMSGh8DSvdmQ07UJp0nv7dMDCiEPcbU0chy4eDruSrYrXt2wrm/s400/Japan-US+GDP+per+capita.png" width="400" /></a></div>
Then, all of a sudden, a recession in 1996 and the <a href="https://en.wikipedia.org/wiki/1997_Asian_financial_crisis">Asian Financial Crisis</a> in 1997 hit, and Japan has been stuck at roughly 73% of US GDP per capita since then (the data from Fred end in 2010, but World Bank has data from 1990 to 2015 that show the same thing). A lot of ink has been spilled in pursuit of an answer to the question of why Japan has settled into a permanently poorer equilibrium, and I'm not sure if I have much to add. I am highly skeptical that demand side factors can depress an economy for more than two decades, especially when better cyclical indicators like unemployment and employment rates tell the opposite story. Japan's demographic transition is also pretty important -- the working age population has been shrinking since the mid '90s meaning that the amount of workers per person (and consequently GDP per person) has had downward pressure for quite a long time.<br />
<br />
Regardless, a 20% reduction in GDP per capita relative to the US is pretty huge, and makes me question my expectation that technologically advanced countries with institutions that don't prevent growth from taking place (think North Korea or Zimbabwe) will unconditionally converge the wealthiest countries. Thinking about this led me to the other major wealth East Asian countries: Taiwan, Hong Kong, and South Korea (Hong Kong is technically a special administrative region in China, but some combination of capitalism and former British rule make it both rich and free enough to count as a separate country in this case).<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhadaRD_qGIdSTTetqZWaXne9FZwY1M47vLqBZsGXzZ5lLoXT_tUtwQBcfVH9pOMsBPwrFMfG___N87fdK29m3K23cIvmnhkflBGY_TRiXGuec3MkLRQ0BzVLhAsqhN-cOeHN9wnmHKWM6A/s1600/East+Asia+GDP.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhadaRD_qGIdSTTetqZWaXne9FZwY1M47vLqBZsGXzZ5lLoXT_tUtwQBcfVH9pOMsBPwrFMfG___N87fdK29m3K23cIvmnhkflBGY_TRiXGuec3MkLRQ0BzVLhAsqhN-cOeHN9wnmHKWM6A/s400/East+Asia+GDP.png" width="400" /></a></div>
As you can see these three countries look a lot like Japan did at various points in the past. If you compare at which year each country was in about the same position as Japan in 1960 (that is about 40% of US GDP per capita), you can see how far behind Japan they are in terms of convergence. Hong Kong is the furthest along, although it's about 15 years behind in its process of convergence while Taiwan and Korea come in about 16 and 20 years behind Hong Kong, respectively.<br />
<br />
Hong Kong and Japan are the two more interesting cases here: both experienced large slumps in the late '90s that lasted well int the 2000s, but then things start to diverge. In the mid 2000s Hong Kong starts to take off while Japan remains plugging along at around three quarters of US GDP per capita. The real question is which is the exception and which is the rule. As a resident of Japan, a small selfish part of me hopes that Taiwan and Korea will eventually get stuck at around the same level as Japan, but it's really more likely that Japan is mired in its own problems and will continue to stagnate while the other countries grow.<br />
<br />
This is easier to see when you look at labor productivity -- GDP per hour worked -- instead of GDP per capita, because things that affect hours worked per employee or the overall employment rate can actually misrepresent the state of convergence.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh-yebCVknyz9eVOsO2Z429ajhpg30Ti53xeEnR_F8O1JsVixddplF8CpqThrK1db7FnI0uHmPjk4U_nx4SDD6w4pI4XvpfJGBLZBtcL7pUjow5thybyP1saj3zmcLBO-NeeBg5RzAJxMNR/s1600/East+Asia+Productivity.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh-yebCVknyz9eVOsO2Z429ajhpg30Ti53xeEnR_F8O1JsVixddplF8CpqThrK1db7FnI0uHmPjk4U_nx4SDD6w4pI4XvpfJGBLZBtcL7pUjow5thybyP1saj3zmcLBO-NeeBg5RzAJxMNR/s400/East+Asia+Productivity.png" width="400" /></a></div>
Labor productivity tells a slightly different story than GDP per capita; while Japan still shows stagnation at around 70% of US productivity after 1996, Hong Kong's recent impressive growth in GDP per capita seems to have been caused by a large increase in either employment rates or hours and Koreans have made up for slower productivity growth relative to Taiwan by working long hours.<br />
<br />
Japan's collapse in GDP per capita in the late '90s seems to reflect labor market problems unique to Japan as opposed to evidence against convergence. Average hours worked in Japan has been declining for decades as people unable to find full time employment switch to low paying part time jobs ("バイト").<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgf1-EqdnKO9RY-zVcgsBFenmTk4W0LCAdoG5irJaE8XQuw9QTnITW8SbNMfElcFi0vLnVA8R9ChcM-CrmstliJI82UblwoyPDAHAchbuJ_my9mN1M3sqEfEgFFIrFCGYKTHDw2ujcsXum1/s1600/Japan+Hours.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgf1-EqdnKO9RY-zVcgsBFenmTk4W0LCAdoG5irJaE8XQuw9QTnITW8SbNMfElcFi0vLnVA8R9ChcM-CrmstliJI82UblwoyPDAHAchbuJ_my9mN1M3sqEfEgFFIrFCGYKTHDw2ujcsXum1/s400/Japan+Hours.png" width="400" /></a></div>
This is probably a symptom of an economy that has been weak for more than 20 years -- the unemployment rate only recently fell back to the level of the late 1990s -- and has little to do with Hong Kong, Korea, or Taiwan. All four regions do face low fertility rates and will likely start being affected by the same demographic transition as Japan over the next few decades, but as long as they avoid a mass transition to part time employment they should look forward to some combination of fewer hours and higher GDP.<br />
<br />
The reason for Japan's slowdown in productivity growth still evades me. I find it hard to believe that it's normal for a country to just stop converging with productivity 30% lower than the US, but I guess Hong Kong, Korea, and Taiwan will be a test of this as they either continue to grow or stagnate relative to America over the next few years.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-32412385508082965212017-06-26T01:04:00.001-07:002017-06-26T01:04:41.885-07:00How Healthy is the US Labor Market?<div dir="ltr" style="text-align: left;" trbidi="on">
The plunge in labor force participation since the great recession in 2008 has led many to rightly question how well the unemployment rate -- the percent of the labor force that has looked for work in the last 4 weeks -- measures the true level of "slack" in the labor market.<br />
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Much (most) of the decline in labor force participation can be explained by the retirement of baby boomers, the oldest of which turned 65 in 2010, and by people between the ages of 16 and 24 choosing to focus on education instead of working.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjzLVafu8JLLMj3SLQcYi6gOHTE4ipXKK24Q69X7lS_Iu4QgLBBJr3Mce3SQv9caNMqaXLJbQjGzbo7XpcnXWA0n76wSGGy45MP3IChK9v2MD8JkCFR3mP9TriR9ZhphDOKt7mUhYFbe3r_/s1600/16to24+civpart.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjzLVafu8JLLMj3SLQcYi6gOHTE4ipXKK24Q69X7lS_Iu4QgLBBJr3Mce3SQv9caNMqaXLJbQjGzbo7XpcnXWA0n76wSGGy45MP3IChK9v2MD8JkCFR3mP9TriR9ZhphDOKt7mUhYFbe3r_/s400/16to24+civpart.png" width="400" /></a></div>
The decline in labor force participation among young people is something that was occurring before the great recession. Even though it the recession seems to have sped up the decline, I'm pretty certain that most of the people between 16 and 24 who left the labor force in 2008 and 2009 or simply haven't joined since then (I'm in that group) wouldn't rejoin even if there was no slack in the labor market.<br />
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While the labor force participation rate for Americans 55 and older didn't actually decline in the great recession, it stopped a decades-long trend upward and has flattened out since then.<br />
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The fact that the participation rate for older Americans has settled at a lower level than participation for the general public, and that the share of the civilian noninstitutional population (basically everyone above the age of 16 who isn't deployed in the military or in prison) that is older than 55 years is increasing, has put significant downward pressure on the total labor force participation rate.<br />
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That being said, it's hard to be certain whether or not the recession has had lasting cyclical impacts on labor force participation, which warrants using statistics other than the unemployment rate to gauge the strength of the labor market.<br />
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One such popular measure is the broadest measure of underemployment put out by the Bureau of Labor Statistics (BLS) -- total unemployed, plus all marginally attached workers plus total employed part time for economic reasons -- or the U-6 unemployment rate.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCFJOEvoYdzSKZ-_hWlyL-QzO7AfTCZKex3dPD2y6XfxGNh0OtV_C-zO5OwJOGvLk4gwO1QYlqX1saDoajAskP_JmDZzlpBOqEl16KEGp6Nh9-R8T3sEAVh4rSYD0gX-2Dr6jKDVEZvfgJ/s1600/U6.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgCFJOEvoYdzSKZ-_hWlyL-QzO7AfTCZKex3dPD2y6XfxGNh0OtV_C-zO5OwJOGvLk4gwO1QYlqX1saDoajAskP_JmDZzlpBOqEl16KEGp6Nh9-R8T3sEAVh4rSYD0gX-2Dr6jKDVEZvfgJ/s400/U6.png" width="400" /></a></div>
I don't really like this as a measure of labor market strength though, because it doesn't count people who retired earlier than they wanted to as a result of the recession, people are only counted as "marginally attached" if they have searched for work in the last 12 months, and part time workers aren't really <i>unemployed</i> (there is an alternative measure that excludes involuntary part time workers but it still has the problems I mentioned above).<br />
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Some people like to look at the employment rate for the so called "prime age" population who are between the ages of 25 and 54 (I don't know why the cutoff is 54, going up to 65 makes way more sense to me) in order to weed out the effects of aging and lower youth participation on the labor market.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjQRYZpiv7BGk287hA9r1qbvFNCpE1cnL2JFAiMVH_24PB_dOEOXH7kf8DzDRuYI_oQ90uzbT3XVFAK3gtov_eJ9dbNRwDWZGWLq217tnLJMRHqkHPh3vUbMJTWcFZlpDOGgUrWC8JZ-0qY/s1600/25to54+epop.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjQRYZpiv7BGk287hA9r1qbvFNCpE1cnL2JFAiMVH_24PB_dOEOXH7kf8DzDRuYI_oQ90uzbT3XVFAK3gtov_eJ9dbNRwDWZGWLq217tnLJMRHqkHPh3vUbMJTWcFZlpDOGgUrWC8JZ-0qY/s400/25to54+epop.png" width="400" /></a></div>
This is a relatively good solution for the years after 1990, and it does show that the labor market is considerably weaker than the unemployment suggests (although not so weak that we need to <a href="http://www.economist.com/Trumptranscript">"prime the pump"</a>), but it has trouble before 1990 because women were still joining the labor force en masse for most of the latter half of the 20th century.<br />
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Basically every statistic that you can easily get from BLS data has a problem like this, so it's really hard to get a good measure of how healthy the labor market is, but there is a solution. The Congressional Budget Office (CBO) looks at the demographic composition of the working age population and comes up with what it thinks the labor force participation rate would be at full employment. It calls this measure the "potential labor force", which tries to estimate the movement in labor force participation caused by gender and aging and can then be used to estimate the cyclical component of labor force participation.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDmYNpVEtsSCF0Hr50QDaWFEm13GyUd_OTQVE6GqGzH9HPHHj3tcIrRraFag4BOPvSNn7SfN7WO8-e-gfYugQ1m4DVVb3s7t6N-mhZr4A4UaVyhRj6xC8uaaK9E5MEqFK-OLinCZfA1Mbk/s1600/Labor+Market+Slack.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDmYNpVEtsSCF0Hr50QDaWFEm13GyUd_OTQVE6GqGzH9HPHHj3tcIrRraFag4BOPvSNn7SfN7WO8-e-gfYugQ1m4DVVb3s7t6N-mhZr4A4UaVyhRj6xC8uaaK9E5MEqFK-OLinCZfA1Mbk/s400/Labor+Market+Slack.png" width="400" /></a></div>
It is then possible to find the "adjusted" unemployment rate with the CBO's estimate of the potential labor force. The above chart shows the actual unemployment rate reported by the BLS as well as my calculation of the adjusted unemployment rate using the potential labor force from the CBO's 2007 and 2017 data for "Potential GDP and Underlying Inputs" (all CBO data is available <a href="https://www.cbo.gov/about/products/budget-economic-data">here</a>). The dashed grey line is the natural rate of unemployment -- that is the unemployment rate that is consistent with full employment -- according to the CBO.<br />
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Since I was only able to find annual "potential labor force" figures, the estimates only extend to 2016, but both the 2007 and 2017 figures are broadly consistent with the prime age employment rate: the unemployment rate overstates the health of the labor market by between 1 and 2 percent (depending if you use the 2007 or 2017 value for the potential labor force). This is similar to where we were in 2003 or 1994, so while there's no real cause to worry about joblessness right now the recovery isn't completely over yet either. As a side note, tax cuts are even more of a <a href="https://www.cbo.gov/publication/52370">stupid idea</a> now than they were in 2003, but that issue deserves a whole post of its own.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-42033904051075710232017-06-21T06:21:00.001-07:002017-06-21T06:21:04.147-07:00Is Raising the Inflation Target Possible (Right Now)?<div dir="ltr" style="text-align: left;" trbidi="on">
Ever since a group of 22 economists wrote <a href="http://populardemocracy.org/sites/default/files/Rethink%202%25%20letter.pdf">an open letter</a> to the Federal Reserve advocating for an increase in the inflation target, economics blogs have been abuzz with <a href="https://mainlymacro.blogspot.jp/2017/06/raising-inflation-target.html">discussion</a> <a href="http://www.bradford-delong.com/2017/06/my-sections-as-delivered-fed-up-rethink-2-inflation-target-blue-ribbon-commission-conference-call.html">about</a> the merits of a targeting an inflation rate greater than 2%.<br />
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While I don't have much to say about the value of changing the inflation target (I pretty much agree with the authors of the letter), I do think there are several practical issues that the Fed would have to deal with if it did want to start targeting e.g. 4% PCE inflation.<br />
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As I see it there are currently two obstacles that make it practically hard for the Fed to increase its inflation target: 1) the Fed doesn't have enough credibility, and would squander what little it has if it tried, to raise inflation and 2) interest rates are so low that providing the necessary stimulus to get inflation to 4% is basically impossible in the short to medium term.<br />
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The Fed adopted a 2% inflation target in 2012 after unofficially targeting 2% inflation for years up until that point, but ironically core PCE inflation has not been 2% since March of 2012 (the headline rate was briefly 2.15% this February).<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghyphenhyphenJtR1L3QmffX06eI_GVpvD4cKzeS_OOrEmytCXQXAbrnqyuBhpM9us1MgTchJQASKUZpDteJlFBNUPQIdLW2DypqckvIZQnYPFV936qmaUC2CYQ3QUvmIzXxQVxDErxIKeotQXBP5RRo/s1600/fredgraph+%25285%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="880" data-original-width="1600" height="220" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEghyphenhyphenJtR1L3QmffX06eI_GVpvD4cKzeS_OOrEmytCXQXAbrnqyuBhpM9us1MgTchJQASKUZpDteJlFBNUPQIdLW2DypqckvIZQnYPFV936qmaUC2CYQ3QUvmIzXxQVxDErxIKeotQXBP5RRo/s400/fredgraph+%25285%2529.png" width="400" /></a></div>
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This consistent undershoot of the inflation has begun to take its toll on the Fed's credibility, with both expected inflation measured by the University of Michigan survey of Consumers and spread between normal treasury securities and inflation protected ones falling below normal levels after 2014.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjYoZCtnl_ZvjZRRYGvjzS0vrVfKmOxJ9Af2iv7w8L4EE4_YAMiw9vesCbO34Le-NgC-68W4baUR1IJxd0U6hD998eJa96X36zn7QZoJtLN4uGLu1t1Ciz5YBe6llT7y8UfGbTcF2oqBnai/s1600/fredgraph+%25286%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="880" data-original-width="1600" height="220" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjYoZCtnl_ZvjZRRYGvjzS0vrVfKmOxJ9Af2iv7w8L4EE4_YAMiw9vesCbO34Le-NgC-68W4baUR1IJxd0U6hD998eJa96X36zn7QZoJtLN4uGLu1t1Ciz5YBe6llT7y8UfGbTcF2oqBnai/s400/fredgraph+%25286%2529.png" width="400" /></a></div>
Since the Fed can't even meet its own low inflation target, what makes anyone think it can meet a higher one? Before we even think about raising the inflation target, we should make sure the Fed is actually capable and willing to let inflation reach 2%. If it that doesn't happen, I'm skeptical that markets and consumers (who are probably too backward looking to expect inflation until they've been experiencing it for a while anyway) will take an increased inflation target seriously.<br />
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Beyond just announcing that it is now targeting a higher inflation rate, say 4%, the Fed would have to take concrete action to raise inflation to its new target. This would involve lowering interest rates considerably, because inflation would now be about 2.4% below target instead of just 0.4%. A useful way of thinking about this is comparing a Taylor Rule with a 2% inflation target and one with a 4% inflation target.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIAKRgoT-hd-MtAB6E9pB0t2OSKDW5B0aCfUMtW2-fI3SuFKqmAXnxjubSX82JSFxaMdyhcy6gz_KaH6ZL-XJps4gI9JVTJju_bxG4QsFpDQSE6sFatYjwecpee9ComGdHc6oJPv1lZ1TY/s1600/fredgraph+%25288%2529.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="880" data-original-width="1600" height="220" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgIAKRgoT-hd-MtAB6E9pB0t2OSKDW5B0aCfUMtW2-fI3SuFKqmAXnxjubSX82JSFxaMdyhcy6gz_KaH6ZL-XJps4gI9JVTJju_bxG4QsFpDQSE6sFatYjwecpee9ComGdHc6oJPv1lZ1TY/s400/fredgraph+%25288%2529.png" width="400" /></a></div>
Here the blue line is the actual Federal Funds rate, while the red line is what a Taylor Rule -- with a coefficient of 1.5 on inflation and 1 on the "output gap" (in this case defined as the difference between the prime age employment rate and its "full employment" level of 80%) -- would suggest the interest rate be with a 2% inflation target. The green line shows what interest rate we should expect the Fed to set given a four percent inflation target. Basically, in order to commit to raising inflation to 4%, the Fed would have to either find a way to make interest rates significantly negative or otherwise go back to the zero lower bound for the foreseeable future.<br />
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I know that even the people who signed the letter weren't suggesting an immediate switch to a higher inflation target, but to the extent that they want the change to happen in the next few years, during which the economic climate will probably remain about the same, it's unclear as to whether or not a quick increase in inflation is actually that possible.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com0tag:blogger.com,1999:blog-5287527236941482415.post-48906013334600715612017-06-15T05:24:00.001-07:002017-06-15T17:32:43.415-07:00Microfoundations, the Euler Equation, and the Phillips Curve<div dir="ltr" style="text-align: left;" trbidi="on">
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Late last night (early this morning for everyone in America?) I had a conversation on Twitter with Noah Smith that got a lot of attention, and later turned into a discussion with with <a href="https://neweconomicsynthesis.wordpress.com/">Jonathan Hyde</a> about the New Keynesian Phillips Curve.<br />
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The actual thread is pretty long and confusing, so I'll just summarize it here. First in a sort of tongue-in-cheek way I asked Noah why economists model agents rationally when they are evidently not rational. He and I then went back and forth about empirical evidence, and I said "Well the Euler equation at least is patently wrong, and the NKPC [New Keynesian Phillips Curve] has trouble explaining inflation since 2008," which led to everyone's favorite tweet of the night (after my <a href="https://twitter.com/jwhandley17/status/875011882247045120">joke</a> about how the models in Physics actually work):<br />
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Incidentally if both Euler equation and NKPC are wrong, then workhorse NK model is basically refuted</div>
— John Handleyハンドリージョン (@jwhandley17) <a href="https://twitter.com/jwhandley17/status/875010702041272321">June 14, 2017</a></blockquote>
This is where Jonathan came to the defense of the NKPC:<br />
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... demonstrated (as far as I can tell) that more plausible models of price stickiness (e.g. menu costs) make any significant difference.</div>
— Jonathan Hyde (@Britonomist) <a href="https://twitter.com/Britonomist/status/875189964207738889">June 15, 2017</a></blockquote>
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While his comment is not wrong, I think it points to one of the main problems with macro: insistence on modelling the underlying factors behind observed phenomena like the Phillips Curve, aka obsession with microfoundations.<br />
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The expectations augmented Phillips Curve has been around since the late 1960's, but microfoundations meant that economists spent years trying to figure out why rational optimizing firms would not adjust their prices instantly -- for a while the debate was between <a href="http://web.stanford.edu/~johntayl/Onlinepaperscombinedbyyear/1999/Staggered_Price_and_Wage_Setting_in_Macroeconomics.pdf">Taylor contracts</a> and <a href="https://research.chicagobooth.edu/marketing/databases/dominicks/docs/2007-menucostsphlillipscurves.pdf">menu costs</a> as a source of nominal rigidity -- but eventually settled with the mathematically tractable hand wave that is Calvo pricing.<br />
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The Calvo model basically says that firms face a constant an exogenous probability that they will not be able to change prices in the next period, so they might set their price too high or too low this period so that they won't be stuck with an extremely suboptimal price next period. This obviously doesn't classify as a "microfoundation" in that it doesn't appeal to a friction that actually exists in the real world.<br />
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In principle, microfoundations might seem like a good idea since they help deal with the Lucas Critique that relationships that appear in the aggregate data -- like the relation between inflation and unemployment -- might disappear when they are exploited. The problem comes when you realize that models with perfectly rational utility/profit maximizing agents don't work empirically. When that fact becomes clear, there are two options: add a whole bunch of implausible assumptions about agents (like Calvo pricing or <a href="http://www.columbia.edu/~ss3501/research/habit_persistence.pdf">habit formation</a>) to make the model fit the data or just go back to modelling things ad hoc.<br />
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Economics has mostly gone with the first approach in the last 30 years, adding tons of parameters (e.g., the fraction of firms that cannot change their prices in a given period, the degree of habit formation, the elasticity of demand for individual monopolistically competitive firms, etc.) to a model just so they can come up with models that behave a lot like the old ad hoc models.<br />
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I don't think that economic incentives shouldn't be considered when making modelling decisions, but frequently models with completely rational agents and utility maximization produce results that go too far. A key example of this is consumption. In <a href="http://jwhandley.blogspot.jp/2017/06/modelling-consumption.html">my last post</a> I showed that consumption is pretty much entirely explained by income and wealth, which is a prediction of the Permanent Income Hypothesis (PIH). Essentially, agents try to "smooth" consumption in the face of shocks to income, so they consume out of their wealth when their income falls and save when income is high. A slight amount of consumption smoothing also occurs <a href="http://scholar.harvard.edu/files/ganong/files/ganong_jmp_unemployment_spending.pdf">when people become unemployed</a>. The consumption Euler equation also predicts consumption smoothing, but to an absurd degree. Whereas <a href="https://informationtransfereconomics.blogspot.jp/2017/06/consumption-income-and-wealth.html">Jason Smith and I</a> found that consumption is highly receptive to changes in income, the Euler equation predicts complete consumption smoothing.<br />
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A more ad hoc consideration of economic incentives and the economic data would lead to a highly qualified version of the PIH that does a much better job empirically than a strict utility maximizing approach. The same thing goes for the Phillips Curve, where assuming rational expectations makes the relationship statistically insignificant (see the t statistic on u_gap, the gap between the unemployment rate and the Congressional Budget Office's estimate of the natural rate of unemployment, in the table below):<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj_zFWzWtcNyxLOX6u7fEBl9bU3PkEJVjxGpXHhE_8RvHO9q4firjY5R9LbpjDVXr0sn1xhmQhpfWKGXS_6bVwspoC_si3arcng83HeKXn3MozMdDQjKuCC7YfggXSmIKte3xk2yo2CqLaV/s1600/NKPC.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="397" data-original-width="625" height="203" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj_zFWzWtcNyxLOX6u7fEBl9bU3PkEJVjxGpXHhE_8RvHO9q4firjY5R9LbpjDVXr0sn1xhmQhpfWKGXS_6bVwspoC_si3arcng83HeKXn3MozMdDQjKuCC7YfggXSmIKte3xk2yo2CqLaV/s320/NKPC.png" width="320" /></a></div>
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Ultimately, in my opinion, the empirical failures of microfounded models show that trying to rigorously model the underlying causes of relationships we see in the aggregate data is a waste of time. Business cycle theory in particular should be more empirically oriented and less focused on logical consistency.<br />
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Update: <a href="https://www.dropbox.com/s/gme4z8q4uwgbzc0/Phillips%20Curve.ipynb?dl=0">here's a link</a> to the code where I compare the New Keynesian Phillips Curve and a backwards looking Phillips Curve to the data.<br />
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John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com3tag:blogger.com,1999:blog-5287527236941482415.post-69103416089585390352017-06-13T04:26:00.000-07:002017-06-13T07:24:28.917-07:00Modelling Consumption<div dir="ltr" style="text-align: left;" trbidi="on">
I was running over things to write about over the next few weeks, and I decided to just casually see how much income and wealth explain consumption. I didn't expect to see anything spectacular, but I pulled the quarterly personal consumption expenditures series as well as disposable personal income and household and nonprofit net worth and ran a regression. The IPython notebook is <a href="https://www.dropbox.com/s/28yzoz89iodfx43/Consumption.ipynb?dl=0">here</a>.<br />
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At first I ran the regression on all the data from 1952 on, and the result actually shocked me -- the first time I think I can say that while referring to statistics -- the R squared value was literally 1. I was too surprised to look at the p values or t-statistics for each variable, but I decided to only look at data after 1990 to see if that changed anything.<br />
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Here's the output for the regression on data after 1990:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEieAqxMXqrEKZL9f0hZqDaP9SHREZ1zDD1fBHCdz7sFGesS3weVyw8ji0C6FZ3B0CW7uM17macJlmlWqcrO0ThtrSZfqT0TLH6-1l3rnM7j6s2Lc0J0x-YqNEQCSGV8dPGGMQEz1jdGlEhh/s1600/Regression.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="404" data-original-width="655" height="245" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEieAqxMXqrEKZL9f0hZqDaP9SHREZ1zDD1fBHCdz7sFGesS3weVyw8ji0C6FZ3B0CW7uM17macJlmlWqcrO0ThtrSZfqT0TLH6-1l3rnM7j6s2Lc0J0x-YqNEQCSGV8dPGGMQEz1jdGlEhh/s400/Regression.png" width="400" /></a></div>
I still suspect that I did something wrong here, but the fit is, in a word, <i>impressive</i>.<br />
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I also plotted the prediction given the coefficients from the regression against the actual data:<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgpDyWDu-9lN4ESxkqt_g-RFc4d8oOwRy_hb4a8sUecZYfNjvlhwfa0ugtcYYwzSAthnNplXs3VhMMFJ52E_2_Jo8tP80zj0-js2Co-KeMnThkPGOXXNFnu-nfcjePlA62irO5QWaX-yyJN/s1600/PCE+Prediction.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgpDyWDu-9lN4ESxkqt_g-RFc4d8oOwRy_hb4a8sUecZYfNjvlhwfa0ugtcYYwzSAthnNplXs3VhMMFJ52E_2_Jo8tP80zj0-js2Co-KeMnThkPGOXXNFnu-nfcjePlA62irO5QWaX-yyJN/s400/PCE+Prediction.png" width="400" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgdbwDkd610_FifAH5PTPxrg4lRnB-QzVIyqKBrj4FzFSOxDuMOqn5niDWtRALyvfN-EwHdYabG9uLYkL8qzYWJhYnbESNjg74_plUjQFEHU5plS2oRw9LtigSkNqWoAvxa2q-csC5HKUri/s1600/PCE+vs+Prediction.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1067" data-original-width="1600" height="266" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgdbwDkd610_FifAH5PTPxrg4lRnB-QzVIyqKBrj4FzFSOxDuMOqn5niDWtRALyvfN-EwHdYabG9uLYkL8qzYWJhYnbESNjg74_plUjQFEHU5plS2oRw9LtigSkNqWoAvxa2q-csC5HKUri/s400/PCE+vs+Prediction.png" width="400" /></a></div>
For good measure, these are the series IDs from FRED I used: Personal Consumption Expenditures: PCEC, Disposable Personal Income: DPI, Households and Nonprofit Organizations; Net Worth, Level: TNWBSHNO.<br />
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Update: I removed wealth from the regression, and the fit is still extremely high. I guess now the question is, if disposable income is such a good predictor of consumption, why does the Old Keynesian consumption function get routinely bashed for being inaccurate? Yes, I know the difference between average and marginal propensity to consume is important, but why insist on the consumption Euler equation given it's almost comical level of inaccuracy while ignoring the startlingly accurate Keynesian consumption function?<br />
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The results of the regression without household wealth:<br />
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Update 2: At Jason Smith's suggestion, I looked at the correlation with first differences (really 4 quarter growth rates) and found that the R squared went down to more normal levels, but that adding wealth does actually improve the fit considerably. The importance of wealth here is a partial win for the Permanent Income Hypothesis but ultimately still a loss for the consumption Euler equation. Here are charts for the new regression:<br />
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John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com2tag:blogger.com,1999:blog-5287527236941482415.post-54482735753326196382017-06-10T05:38:00.000-07:002017-06-10T05:38:07.663-07:00Monetarism and the Neo-Wicksellian Framework<div dir="ltr" style="text-align: left;" trbidi="on">
I know I'm about a year late to the party, but recently I have been listening to David Beckworth's <a href="https://soundcloud.com/macro-musings">Macro Musings podcast</a>. Two interviews that particularly caught my attention were the one with <a href="https://soundcloud.com/macro-musings/nickrowe">Nick Rowe</a> and the one with <a href="https://soundcloud.com/macro-musings/braddelong">Brad Delong</a>. In the ten months since Brad and Nick were on the podcast the world has been too preoccupied with Donald Trump's antics and, more recently, the snap general election in the UK to do much discussion of economics, but now I want to talk a little bit about the relationship between monetarism and new Keynesianism.<br />
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Both Brad and Nick argue when talking to David that new Keynesians are really all monetarists, or, more specifically, that in the 1990's everyone agreed that economic fluctuations were caused by disruptions in the demand and supply for money and that the big question was what rule should replace Milton Friedman's k% rule for monetary policy. According to Nick, the absence of money in new Keynesian models is really just implicit because if the model had no money (i.e. if it were a barter economy) agents would just "barter their way back to full employment."<br />
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I think the idea that recessions are just excess demand for money is interesting, especially since it applies even in the very Keynesian context of IS-LM. With the LM curve relating real money demand to output and the interest rate, it is clear that shifts in the IS curve are the same thing as higher demand for money at a given interest rate. If we write the LM curve as M/P = L(Y,r) = aY - br and the IS curve as Y = c - dr, then we can figure out what happens if a recession hits -- in this case that means c falls. In a normal IS-LM diagram, the IS curve would shift left, and both r and Y would fall, but if you look at it slightly differently by holding Y constant given the fall in c, you can see that a shift in the IS curve just changes the level of r for a given Y. Substituting this back into the LM curve shows that money demand for a given level of Y has increased: M/P = aY - br = aY - b/d(c+Y) = (a - b/d)Y -b/dc.<br />
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That might be really confusing, and I apologize for not being able to explain things <a href="http://worthwhile.typepad.com/worthwhile_canadian_initi/2015/08/on-defining-recession.html">as succinctly as Nick can</a>, but basically I'm saying that recessions (drops in aggregate demand) are just increases in the demand for money (given the level of real GDP) that are not met with increases in the supply of money. Since the quantity of money demanded must equal the quantity supplied, output falls to reduce money demand to the appropriate level. That's why if c falls by, for example, 10 in the model above, then the real money supply must increase by b/d*10 for output to remain constant.<br />
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Bringing expectations into the money demand function makes things a little more interesting. Let's say money demand increases when inflation expectations are low because, per the fisher equation, low inflation expectations mean low nominal interest rates and low interest rates cause less incentive for people to hold interest bearing assets in place of money. In this case, if something causes inflation expectations to fall precipitously, money demand will increase and, absent central bank action to increase the money supply, a recession will occur. If, as is true in most cases, central banks have control over inflation expectations in the medium to long term, they effectively have the power to shift around the demand for money. Thus, monetary policy can take two forms: open market operations and expectations management.<br />
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This is where Neo-Wicksellian comes in. I've written a little <a href="http://ramblingsofanamateureconomist.blogspot.jp/2016/03/a-defense-of-neo-wicksellian-analysis.html">bit about this before</a>, but monetarists usually prefer the money demand/supply description of monetary policy because they see interest rates as a bad indicator of economic conditions (never mind that wild swings in money demand also make most measures of the money supply bad indicators of economic conditions). I, however, think that the monetary explanation of business cycles and the Neo-Wicksellian description are very similar, but that using interest rates has a couple of distinct advantages.<br />
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In its simplest form, the Neo-Wicksellian framework just says that if the central bank sets a nominal interest rate above the natural interest rate, there will be a recession and vice versa. Thus, with a relatively constant natural interest rate, high interest rates lower aggregate demand while low interest rates raise aggregate demand. The problem is that the natural rate of interest -- which you could consider as the level of r that keeps Y constant in the IS curve above -- fluctuates around a lot, which makes interest rates look procyclical.<br />
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Another important thing to notice is that central banks can influence the natural rate by changing inflation expectations, which is basically the same as how they change money demand. In way, the Neo-Wicksellian framework in which recessions are equivalent to interest rates above the natural rate of interest and the "monetarist" view in which recessions are excess demand for money are basically the same thing, just with the focus on different variables.<br />
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The Neo-Wicksellian view does have one advantage in my opinion though: it more accurately shows constraints on monetary policy. In the monetarist view, the solution to a shortfall in aggregate demand is always more money, but the Neo-Wicksellian view shows that there are constraints to monetary policy, at least in the present. If the natural interest rate falls below zero, the central bank no longer has the ability to just cut interest rates/just increase the money supply to ward of a recession. At this point, the only way a central bank can end the shortfall in aggregate demand is to increase expected inflation so that the natural interest rate is no longer negative. This is why increasing the monetary base from about $800 billion to about $1.7 trillion didn't stop GDP from collapsing in 2008.<br />
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Given that Neo-Wicksellian and monetarist frameworks both work as ways of looking at the same IS-LM model, I don't know how valid it is to say that everyone became a monetarist or that everyone became a "new Keynesian" in the 1980's and 1990's. It seems like there really isn't that much difference between either group in the first place. At least over the last few years, the real split in economics seems to be between people like John Cochrane who are skeptical of sticky prices and that fiscal policy can raise aggregate demand at all and everyone else.</div>
John Handleyhttp://www.blogger.com/profile/16057855086740377031noreply@blogger.com2