Has Policy Uncertainty Slowed the Recovery?

Nicholas Bloom discusses economic policy uncertainty and its effect on the recovery (video, 31:06).

Dr. Nicholas Bloom discusses economic policy uncertainty and its effect on the recovery. What is economic policy uncertainty, how do we measure it, and what causes it? Secular movements in policy uncertainty over the last 25 years offer important clues as to what to expect in the next few years.

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00:00:11 So, I’m going to turn to something, I guess that’s been previewed a bit by Oscar and Mark Zandi, policy uncertainty. I should say, this is joint work with Scott Baker who’s a graduate student at Stanford and Steve Davis who probably many of you know at Chicago. So, policy uncertainty has definitely grabbed a lot of press media and policy attention recently. So here is a screen shot from

00:00:31 the front page of the Wall Street Journal a few months ago shows Olivia Blanchard from the IMF, launching a world economic outlook, they put this out twice a year. And the IMF and the Fed, for example, I know John Williams has been taking a similar line of arguing that the policy uncertainties is a major drag on growth around the world and the U.S. I should say so, not everyone agrees. Paul Krugman disagrees, Paul Krugman being Paul Krugman when hedisagrees, he disagrees

00:01:01 pretty strongly with words like culture of fraud and the uncertainty scam. He doesn’t really hold his punches, Paul Krugman. Now of course if Paul Krugman disagrees, FOX News disagrees with Paul Krugman’s disagreement. So I guess that puts FOX News on our side. So I don’t really know which way to make of this. What I want to do today is get between the disagreement and the disagreement with the disagreement. The disagreement with the disagreement and come to some kind of

00:01:28 sensible conclusion. So what I’m going to go through today is trying to methodically measure policy uncertainty then talk about our measure, how reasonable does it look and, you know, I’ll argue that we have a measure of policy on certainty, it’s reasonable, it’s not perfect, but it is workable. And then finally the most important point is, what’s the impact of this on the recovery? So how important is it going to be? And I’m going to argue that Policy

00:01:53 Uncertainty has been a factor, it’s probably not the largest factor, but it’s definitely one of a number of factors that’s been holding back the recovery. So I’ll go through these one by one. How do we measure policy uncertainty, well I’m going to construct an index and our index has four components. I’d like to think of it as a data sausage. I guess being British we eat a lot of sausages and I always warn before you eat a sausage try and find out what’s inside the sausage. Sausages are normally made that way to hide what’s inside them. If anyone’s been to Europe recently you should be particularly alert about eating any meat products.

00:02:30 It’s not clear what animal let alone whether it’s mammalian, I think is in some food products. So I am going to try and go through our data sausage to assure you that there’s no horse meat at least in our data sausage. So the first thing I’m going to talk about is the news-based index. About half way or half of our index

00:02:48 is going to be based on newspaper coverage of policy uncertainty, I’ll talk about that for a bit. And then there’s three other components, two of which are forecasts of disagreements, or how the forecast has disagreed about government expenditure and the CPI inflation. The idea being they disagree a lot, it suggests people are very uncertain. And then finally tax cut expirations. Everyone’s heard about the fiscal cliff, well can we put numbers to this? And we do and this is a final component of the index. So

00:03:15 firstly, what about our news-based index? Well, to generate the news-based index what we’ve done is we’ve taken 10 major U.S. newspapers, so the New York Times, the Wall Street Journal, the USA Today, Washington Post, for example and looked for the frequency of three terms in the article. One is the words economic or economy, the second is uncertainty or uncertain and the third is six policy words, so regulation, deficit, Federal Reserve, congress,

00:03:42 legislation or White House. And we divide the count of these words in each month by the number of newspaper articles in that month. Why do we do that? Well, just the volume of news per month is changed over time. For example, the cost of paper goes up and down and we want to make sure we control for that. And for each

00:04:01 our 10 newspapers we normalize some type of standard deviation of one and add them together. So in a sense this is basically an average frequency of how often newspaper articles appear to talk about policy uncertainty. What does that data look like? So here’s the graph. We’ve normalized this again to 100 prior to 2010. The growth basically looks pretty sensible. So we start in ’85. I’ll

00:04:24 show you some more historical data in a bit. There’s a spike around Black Monday, why is there a spike then? Well after Black Monday there’s probably, you know, many of you remember there’s a lot of debate about whether it’s necessary intervention in the market. There was some policy uncertainty. Gulf War won clearly a lot of political uncertainty there. You know, the Clinton election was a pretty close call. LTCN, you know, some of the 911 Bush

00:04:46 election. But most obviously there’s been a big surge recently. So anyone that’s been paying any attention to the news at all will have noticed the newspapers are full of articles about policy uncertainty. And we’ve picked this up in our index. It’s been bouncing up and down. The high point was August 2011 around the debt ceiling debate in Europe, dropped back down again and the fiscal cliff at the end of December 2012 another high point. It’s dropped down a little bit, but it’s still pretty high. So the newspapers are definitely full of stories about economic Policy

00:05:13 Uncertainty. What about the next two components, disagreement. Well, here is one measure. What we look at as we go from the Philadelphia Federal Reserve Bank has this quarterly forecast data base and what forecast is forecasting about government expenditure, there’s about 50 of them. And we look at the interquartile range we compare basically the 75th high forecast with low and we look at the gap between them. The idea being that the

00:05:37 gap’s really wide, there’s a lot of disagreement and the gap’s really narrow, there’s not much disagreement. And to scale this we normalize it by GDP. So it’s basically how much disagreement there is over the amount of state and local expenditure. And again, we see to some extent in this graph you see a bid of a u-shape. There was a lot of disagreement over the amount of government expenditure in forecast people didn’t know what

00:06:00 was going to happen, there’s a budget, Balance Act, you know, the Budget Enforcement Bill, Clinton’s election. The early’90s, mid ‘90s were a period of pretty low disagreement, pretty high certainty. We see that in a number of measures actually. The ‘90s were a period of relative common, many measures of volatility and uncertainty as were the early 2000s. And then more recently there’s much more disagreement. Not surprisingly it’s much harder to forecast what’s going to happen in future with things like the fiscal cliff and the

00:06:28 sequester bill. The other measure we look at is CPI, Consumer Price Index is basically a measure of uncertainty around, it’s a measure of inflation. If we look at disagreement around the CPI this was very high in the second half of the ‘80s. Why was this? Well this came after the Volker period. So, you know, the beginning first half of the ‘80s was pretty unusual, extremely high interest rates, inflation had been getting out of control. It was

00:06:55 much less obvious what was going to happen for inflation going forwards. But over time disagreement falls down, inflation becomes more predictable, in a sense for a bank more boring, a good thing. Inflation forecasts are relatively stable. There’s relative agreement. But more recently it’s bumped back up again. So as another measure of uncertainty there’s much more disagreement about what inflation rates are going to be going ahead. Finally, we look

00:07:22 at tax code, so how much tax code has been scheduled to expire. The way we do that is we get data from the Congressional Budget Office, they put out every year an incredibly useful analysis of the government budget. And at the back of it, like Oscar I like data, if you burrow through to the back of it there’s tables which break down government expenditure in a couple of ways. One looks at what the government will spend if it maintains all its current policies. And the other says what the government is going to

00:07:53 spend if you assume polices expire as they’re scheduled to. And the difference between them gives you an idea of how much taxes are about to expire. And here a plot of the discounted difference between them. So what we do is we look at tax code, we discount the amount of tax code that’s about expire by 50 percent next year, by, you know, 50 percent squared the year after and out into the future. The idea is we care a lot about tax code that’s about to

00:08:20 expire in the near term, so people don’t care that much about tax code that’s going to expire. Five years from now it’s beyond the current congress anything could happen. You certainly care a lot about tax code that’s about to expire very recently. What we see here is a huge, tsunami, a tidal wave of tax code about to expire. So there’s data only in fact goes back to 1991. When I asked Doug Elmendorff about this, the reason was they didn’t break the figures down separately between scheduled and actual data before 1991

00:08:49 because there was no issue about expiring tax code. So it was basically zero before here. There was a bit of a bump here. This was the accelerated depreciation allowance after the 2001 recession and 9-11. Things calmed down again. And then here, this is the buildup of the Bush tax credits, the temporary employer tax credits up until the end of 2012. So at this point here there is an enormous amount of tax code about to expire. December 31st

00:09:18 a lot of the tax codes we got rid of will be made permanent. But even so now the amount of tax uncertainty is a relatively high level compared to prior to 2008. But compared to recent periods it’s pretty low. So tax uncertainty has been high. Vast amount of tax code about to expire, much of it is being made permanent at least

00:09:39 in the near term. So then we combine these together, you know we form our sausage, we take each component of the standard deviation one and then add then up, what do we find? So this is our overall index of policy uncertainty. Again, it looks relatively similar to the news index. It’s based on a similar, you know, the news index is half the underlying weight. Couple of things, the one you see, you know, as going back big spikes for policy uncertainty.

00:10:05 But, you know, the two stylized facts that A, there’s been a large increase recently. So from the interest rates cuts in beginning of 2008 and the stimulus bill, policy uncertainty has risen pretty highly and B, it’s not come down. So it’s both risen up and stayed pretty high. Mark asked me earlier what the most, this goes up to December 2012, we release this stuff monthly so he put out

00:10:28 March’s figures just a couple of days ago. It’s drifted down a little bit, but it’s still relatively high. So the current numbers are in the mid 150s. So policy uncertainty is certainly not as high as it was in December 2012 or in the summer of 2011, but for anything prior to 2007 it’s pretty high. I mean it’s not much below, for example, in numbers after 9-11. So we still are in, at least according to our index an era of pretty high political uncertainty.

00:10:54 And I guess that’s not surprising given all the debates about budget and to some extent regulation. So, you know, one question is what is this picking up? Another measure people often use for uncertainty is stock market volatility. So, you know, most people are probably familiar with the VIX so just to explain for those of you that aren’t, the VIX is a one month forward looking measure of stop market volatility. It’s basically pulled out of options prices.

00:11:21 It looks one month ahead, you know people have used stock market volatilities to measure uncertainty. Are these two the same? Well, surprisingly the answer is they’re correlated but not as much as you think. So my view before looking at this is look, the stock market is picking up policy uncertainty partly, but actually over the last two or three years stock markets have been relatively calm. Stock market volatility surged in 2008 and 2009 was very high along with our policy uncertainty measure. But the VIX in red has fallen to pretty low levels. In fact, right now it is close to

00:11:53 all time low levels. So stock markets now are very calm. Policy uncertainty is very high. So what’s driving this? Well one factor that seems to be going on is policy uncertainty is more medium in long run. What are the things we care about? We care about balanced budgets, about tax and spending, regulatory reforms. Most of these are several years out. A lot of this isn’t, you know, one month out time horizon. We can gather that if we look at

00:12:20 different data. So from Goldman Sachs they have some proprietary data we got hold of. In green is ten year implied volatility on the stock market. So the VIX there was one month ahead. This is ten years ahead, it’s a much longer run time series. This has stayed pretty high. So our policy uncertainty measure is high and ten year out stock market volatility numbers are high. So one of the differences with the stock market, the stock market is relatively calm right now not because stock, the financial markets aren’t

00:12:47 concerned about events being uncertain, they are. But they’re concerned about them in the medium and long run and not picking these up, at least in the day-to-day basis. So what about other countries, we have discussed Europe, we’ve looked at this in a number of other countries. One of the interested stylized facts is around the world there’s recently been a big surge in policy uncertainty. It’s not the same driver in every region so China, a lot of this is the leadership change over that happened recently. Here is Europe, Europe went into recession slightly later and looks

00:13:17 like it’s come out of recession and it’s taking longer to recover. Here’s our index for Europe. You can see that European policy uncertainty, which we use based on 10 European newspapers has surged in 2008. Before then it had its own rhyme and reason, you know. There was the Nice Treaty, there was some of the European treaties drove European policy uncertainty up, but in the most recent four years it’s gone as has data for India has its data

00:13:42 for China, has its data for Canada, Japan, etcetera. So in the most recent three or four years, policy uncertainty is definitely a U.S. phenomena, the interesting thing is we should come back to why the U.S. is high, it is also high in a number of other countries. And I think part of the issue is tough decisions generate policy uncertainty. When governments are faced with difficult decisions around cutting, spending or raising taxes it makes the decision making hard and that seems to generate much more policy uncertainty. So, you know, if we drill down in the U.S. numbers, what’s going on? What are we talking about in terms of what are the policies in particular? This graph goes through and I’ll go

00:14:20 through the numbers and give you the headline, but in terms of drill it down what we’ve done is we’ve looked at our policy uncertainty and we’ve broken it down into various sub periods and normalized it to 100 overalls. So this is an overall measure in the most recent four years, it’s about 30 percent above its long-run average before then it was a bit below it. Now, what we want to know is, what are

00:14:39 the factors driving it. So one of the potential factors obviously of most interest, I guess to the Fed is monetary policy. So is it monetary policy uncertainty that’s been driving the surge in policy uncertainty overall? Well, to look at this we can go back to the news database and say, what share of newspaper articles that

00:15:00 talk about economic policy uncertainty also mentioned words to monetary policy. So interest rate, you know, federal funds rate, federal reserve, inflation, et cetera. Turns out on average across all, you know, going back to 1985, basically 30 percent or about one third of articles about policy uncertainty also mentioned monetary policy so certainly monetary policy is a big factor. Interestingly though that hasn’t risen in the last four years. So over the last

00:15:28 four years if you read these ten newspapers they are not talking particularly more about monetary policy uncertainty than they were before then. Why is that? Well, our interpretation is interest rates have been low, inflation rates have been low, inflation rates have been low. And while economists, I guess like us, concern ourselves very much with QE and operation twist, et cetera, the general press in terms of the press and the public are not particularly concerned in monetary policy uncertainty. As far as

00:15:54 they’re concerned inflation interest rates are low, you know, there’s definitely discussion of it in the press, but it’s no higher than it was before. So monetary policy uncertainty doesn’t appear to be driving this. I guess, you know, this is the right audience to be saying that message. So maybe I should say that again, but in terms of what is going on, what is driving this, well what seems to be driving, you can imagine who the usual suspects are, taxes, spending and regulation. Tax policy uncertainty gone up massively in the newspapers is full of articles about taxes, spending and then

00:16:28 regulation, particularly healthcare and various entitlement programs. Interestingly, despite the time the three of us has spent talking about this, Europe doesn’t get much coverage. So, here’s the coverage about silver in debt and currency crisis, it’s gone up a lot, it’s actually gone up tenfold over the last few years, but basically from a very low base. Why? You know, Americans don’t care about much else outside of America. American newspapers don’t talk about Europe or anywhere else, they basically talk about America. So even a tenfold increase in discussion of Europe from

00:17:01 the base is so small it doesn’t seem to be driving our index up. So it’s basically American taxes, American spending and regulation, in particular healthcare regulation. How do we evaluate this, you know, I’ve shown you a bunch of data. These numbers look sensible. Well there’s a couple of things you may worry about. One is suitability. Can you learn anything from the newspapers at all? These are the San Francisco Chronicle is in there, these are ten

00:17:29 respectable newspapers, the LA times, there a couple of California newspapers, the regional spread. But are they indicative? And secondly accuracy, are these newspapers reliable? I mean everyone has their favorite story. I guess many of us will speak to journalists pretty regularly. I guess the journalists I speak to seem to be pretty reliable. But you worry about taking mass indexes of them. So, one of the suitability tests we do is we say, well look, imagine

00:17:55 you wanted to measure stock market uncertainty, something we can actually see in the data because we have the VIX index. Imagine we set out in the newspapers to measure that. So we did the same process we’ve done for policy, but rather than looking for words around policy we looked for stock market words like stock price, equity price or stock market, what do we find? Well we find if you try and measure stock market uncertainty using newspaper searches we actually do a pretty good job. So if you wanted to use newspapers to measure stock market uncertainty that’s what we have in blue our financial uncertainty index from the newspapers

00:18:27 and here’s the VIX in red, they’re pretty correlated. In fact so correlated we’ve been publishing this data, you know, I know it’s been downloaded by various hedge funds and banks as kind of an indicator of stock market uncertainty. So newspapers are good for looking at stock market uncertainty. Another very obvious thing to look at is unemployment. So we also know what unemployment data looks like. Is it true that newspapers mention the word layoff, unemployment or job loss more frequently than unemployment’s high. The answer again, is yes, very much so.

00:18:55 So again, for a very obvious economic indicator newspapers do a pretty good job. So you know, on a couple of suitability tests, newspapers seem to be able to measure broad based indicators over time. The other thing we did is we performed a painful audit so one of the advantages of being a professor is you have a large supply, a very eager, very bright and relatively under paid workers at your disposal, called undergraduates. And we had six undergraduates read three-and-a-half thousand newspaper articles about policy uncertainty. So if anyone has any kids at Stanford that have been

00:19:33 complaining about a somewhat unusual and repetitive research assignment then you know exactly what they’ve been working on. So we had six undergraduates, they read three-and-a-half thousand newspaper articles, which I can say honestly isn’t that bad compared to what else goes on this isn’t that bad a job. They had to read the newspaper articles at the end of the newspaper articles we gave them a guide. They had to basically say is it really about economic policy uncertainty in which case our computer

00:20:00 algorithm has done a good job, or is it one of two problem cases? So one is a false positive when it’s not about policy uncertainty but the computer thinks it is. My favorite article we came up on this was there’s an article about this woodpecker that was going extinct and they said they were uncertain of whether the woodpecker was extinct, which pulled the uncertainty word. And it may affect the local economy and they weren’t clear whether they were going to

00:20:25 legislate on the mining companies. That tagged as economic policy uncertainty, but clearly it was nothing to do with an impractice. Then there are obvious false negatives. For example, if someone uses the word ambiguous rather than uncertain we don’t pick it up but clearly if that policy is ambiguous it’s talking about policy uncertainty. So we kind of systematically drilled into the data, what did we find? And I won’t go into the details, but basically the undergraduates stay aligned pretty well, the correlation is about two-thirds, not perfectly, but it’s a reasonable measure. The other thing having started recruitment issue be concerned about a bit

00:20:57 is political bias. So, you know, for example the Wall Street Journal has clearly been taking a stronger line on policy uncertainty than many of the other newspapers over the last few years. Is that representative of the Wall Street Journal is more aligned I guess to the right to the Republicans than some of the other newspapers is this a similar general phenomena? Well the answer basically, no, we can split out ten newspapers using there’s a media I don’t want to say bias, a media slant measure that breaks newspapers down

00:21:27 into more Republican and more Democrat. The difference between then and you know how much they talk about policy uncertainty is not very big, it doesn’t explain much to the gap so it’s not the case. But all the republican newspapers are whipping up a storm of a policy uncertainty recently and that’s what’s going on in our measure. Republican and democrat newspapers are basically full of stories about policy uncertainty for the last few years. So finally, what’s the impact? Well, the literature has three channels. If you look at the theory, what are the three theories out there? Well one, you know, the most obvious theory in some sense goes

00:22:02 back to a paper by at the time a little known assistant professor in Stanford called Ben Bernanke whose PHD paper is actually on real options affects of uncertainty, so you know, and Sylvain Leduc and Zheng Liu have been some more recent work on this, the bank has been doing more recent work on this. The idea here is if your business and you’re uncertain you’re reluctant to hire and you’re reluctant to invest. I mean it’s very intuitive, you wait for, you know, see how things will turn out. So this is called the real options effects, there’s a second angle which is financing costs,

00:22:32 which, you know, links most obviously the example of what Oscar is talking to earlier on financial crisis. They could be linked, but uncertainty pushes out risk premium. And thirdly is an angle on precautionary savings if people are uncertain they reduce consumption and improve their balance sheets and you’re going back to market at the beginning, firms can do this as much as individuals. So they’re the three channels going on. There’s a

00:22:54 lot of evidence, often for the first channel. So this is the kind of classic anecdote you hear. So David Cote who was chairman and CEO of Honeywell. I guess he’s not in the room before I continue to read okay, he was chairman and CEO of Honeywell a Fortune 500 company employing 130,000 people stated back in the end of last year right now we’re holding back on all but the most necessary external hiring. And on capital expenditures if I can make the decision now or six months from now I’ll make the decision six months from now and see what develops. So, you

00:23:25 know, this is the classic story. Everyone is waiting. What’s the evidence for this? Probably the best evidence is frankly from surveys so the chamber of commerce reported that more than half of small businesses cited economic uncertainty as their top concern mid last year. There’s an annual global CEO survey that came out late last year in every region around the world their top concern was uncertain volatile economic growth. The National Association of Business Economists said, the vast majority of panelists feel that uncertainty about fiscal policy is holding back

00:23:59 the pace of the economic recovery. So a lot of survey evidence. Probably the best evidence actually comes from your own Beige Book, the FOMC Beige Book, so this is about a 15,000 word survey that the Federal Reserve system puts out a couple of weeks before each FOMC meeting. So to summarize in words what they’re feeling is about the state of the economy at that time. It’s very useful and what’s great is you can search online in the Beige Book for the count of the word uncertainty and then have another

00:24:28 undergraduate go back and read every time the word uncertainty was mentioned, read in what context was it. It’s pretty clear mostly, you know, is it uncertainty about demand or is it manufacturers in Texas claim they’re uncertain about the state of government demand from the healthcare service. And here you can see the count of frequency of uncertainty and on the policy context and this is clearly searched recently. So according to the Beige Book this is the January 2013 one. If you read this it’s full

00:24:57 of comments about policy uncertainty, comment after comment talking about people want to invest, they don’t want to hire, they’re uncertain about the sequester, they’re uncertain about taxes, they’re uncertain about healthcare regulation, just you know, it’s a kind of a frightening read in a sense. We can take the Beige Book and you can drill down a bit further and ask about what are the things they’re complaining about? We broke it down into a bunch of categories and interestingly category A was monetary policy, which apparently is not uncertain at all according to the Beige

00:25:27 Book. So that’s so zero it’s not even up there. We always laugh it’s clearly been very carefully written. But it is, at least the level is consistent. The level is consistent with newspapers. I mean I agree that monetary policy uncertainty hasn’t gone up even if I don’t disagree it doesn’t exist. But what the Beige Book talks about is the same thing again, fiscal policy, taxes, spending and healthcare regulations, they’re very consistent. Finally we can look at VARs, you can look at estimations, they’re very similar to what

00:25:55 Oscar showed you. You can ask the question, if you went from the level of policy uncertainty in 2006 the last clean year before the recession to the level in 2011, which is kind of one of the higher levels, what would that predict statistically would happen to industrial production and employment going forwards? The prediction is over the next year and a half it would predict on average industrial reduction by about four percent, employment falls by about two-and-a-half million. So this is a sense in which these predictions are reasonable, but then definitely not the whole story. So, these magnitudes are reasonable, they’re not massive.

00:26:29 You know, one concern is have I fettered around with the statistics? You can run these kind of estimations in a whole lot of different ways. The numbers look pretty similar so it’s not about how you play around with the data. A bigger concern, which is actually what Paul Krugman was raising at the beginning in his articles was it’s not clear what’s cause and effect. So the most obvious concern is the government sees the economy tanking starts cutting taxes, raising expenditure that generates

00:26:57 uncertainty and then the economy tanks. So it’s not clear whether the government is looking ahead doing policy stuff and that’s what is generating this relationship or is really policy uncertainty is a problem. My view is pretty consistent with Goldman Sacs and some of the other banks. I don’t exactly know what Mark’s view—Moody’s is, but Goldman had a piece that came out in a fair amount, kind of encapsulated our view, which is from 2008 to 2010 policy uncertainty is very high. I think that’s the outcome of policy makers trying to address the terrible economic state. I agree broadly with what was done monetary

00:27:34 policy, you know, is exactly right to try and be as accommodating as possible, fiscal policy, I think was, you know, correct to try and be accommodating. From ‘11 onwards it’s much less obvious. My take is from 2011 on which the political process to some extent has let us down. It’s a difficult situation. The UK is not doing a lot better so, you know, it’s not the Americans do not take well to being told what to do by people with accents like this. So I have

00:27:58 to be careful. But you know, it does feel like in the data and the surveys said, yes, the policy uncertainty has been a problem from 2011 onwards. And I think it’s holding back the recovery. Recently in our end, I have two minutes left, we’ve been extending the data back using the almost the same ten newspapers back to 1900. It’s a fascinating exercise, it’s kind of thing you can do as an academic. And one of the things you see is in the Great Depression policy uncertainty as we measure was very high. But it

00:28:29 only spiked after Roosevelt came in ’32 and started the New Deal. So it is not the case of terrible recession on the same as increases and policy uncertainty. The recession was a couple of years in the making before Roosevelt came in and changed stuff around very fast. In the most recent recession I guess Bush initially and then Obama did a lot of very active policymaking right at the beginning, which is we saw it rising. But you know, recessions don’t necessarily lead to policy uncertainty. The more striking thing you see is that our measure of policy uncertainty has been steadily climbing from the ‘60s up until now. So, you now, I’ve been

00:29:00 showing you data like this but actually if you look back there’s a secular rise over the last forty years. Why is that? Well, there are a number of different stories and some of them are political. But two obvious economic stories are one is government expenditures share the economy have just been going up and up and up. So government expenditures that share the economy has gone up from about 25 percent in 1950 to 45 percent now. And if the government is almost twice as big a share of the economy

00:29:27 government policy uncertainty becomes a much bigger deal. So as government gets bigger policy uncertainty becomes more important. And it’s not just expenditures gone up the other almost more scary thing is this, so there’s something called the Federal Register which all policy has to be recorded in and you can just do a page count of the Federal Registry going back to 1936. If you do that the number of pages in the annual Federal Register has gone up tenfold. There is more than ten times as much policy coming out and it’s pretty highly correlated with policy uncertainty. So as

00:30:01 governments get bigger they spend more money, they make more regulation, they set more laws, this induces more policy uncertainty. So to conclude if you interested we have a lot of the data. We put the daily, we have a daily index we put up at 9:00 am EST every day and monthly day can be put up on a number of countries on the website. You know, I should say, policy uncertainty appears to have risen a lot since 2008, it’s pretty high. The evidence suggests it’s holding back the economy. You know, I

00:30:27 think it’s a factor, I doubt it’s the largest factor. I think there’s evidence it is a factor. As interestingly for me in the bigger sweep of things it is really high right now compared to going back, you know, from the ‘60s and back. And it is one of the phenomena I think that’s come from the expansion of government. I’m not particularly against, I’m not making argument pro or against expansion of government, but you know, a side outcome is policy uncertainty seems to be a bigger issue. Okay, thanks.

00:31:06 [end of recording]

About the Speaker

Nicholas Bloom is Professor of Economics at Stanford University and Co-Director of the Productivity, Innovation and Entrepreneurship program at the National Bureau of Economic Research. Dr. Bloom's research focuses on understanding the economic impact of uncertainty, such as that which followed the 9/11 terrorist attacks and the Cuban Missile Crisis. He is also constructing an empirical basis for understanding what factors drive differences in management practices across regions, industries, and countries, and how this determines the economic performance of nations and firms. Dr. Bloom is the recipient of an Alfred Sloan Fellowship, a National Science Foundation Career Award, and the Frisch Medal, awarded by the Econometric Society.

Dr. Bloom has a BA from Cambridge, an MPhil from Oxford, and a PhD from University College London. He previously worked at the UK Treasury and McKinsey & Company. See his research page.