The problem with this entire discussion is that we use terms like "wages" and "productivity", which have meanings in the English language, and associate them with metrics which are utterly divorced from those meanings. To have a sane discussion, we're forced to use these shorthands, but the fact of the matter is that if we spelled out what we were actually measuring it would be very clear that all of these phenomena being measured refer to things disconnected from any of our actual experience.
Even more so, the methodology for most of this data has changed so much over time, with so little overlap between methodologies, that we have literally no idea what the state of the world was even a few years ago. All we have are a mixture of giant measurement artifacts, and when two of them correlate we celebrate because we might have found a metric that can bridge the divide between methodologies, but that correspondence disappears as soon as we try to find out if there are systemic changes -- our ability to determine whether something has changed has an implicit reliance on the assumption that nothing has changed, so all of these arguments become circular.
Econometrics is a philosophical dead end that just ends up producing broken policies disconnected from reality and causing us to make up a new suite of politically-motivated metrics to match the outcomes that we're looking for, and then give the metrics names that refer to things that have intuitive meanings and pretend we've found insight.
You really have to go back to non-econometric-based economics (the Austrians, von Mises and Hayek) to get any sort of insight into how economies can be made to work at scale, and the answer is that we don't understand them, and that technological progress and population changes mean that attempts to push them in a direction will have side effects that far outweigh any of the attempted influence.
This isn’t true, the study of applied economics (new Keynsian) saved the US in 2008 when the Fed decided to shore up liquidity and helped bail out industry in concert with the government. Austrian policy would’ve let the entire system collapse and rebuild itself to avoid the construction of perverse risk incentives and the zombification we are seeing in the economy today. You can argue which would be better long term (I think Austrian) but short term we needed Keynesian measures to save jobs and lives from being consumed in a downward spiral of debt chain triggering and collection.
Productivity has a precise economic definition - ratio of output to inputs - and correlates highly to standard of living. We don’t fully understand how and why technology advances, but we measure increased technology through a variable called the solow residual. Economic policy can help lead to technology breakthroughs that increase productivity and the standard of living. It’s very shortsighted to dismiss economics out of hand as something we don’t understand. A lot of it is politically motivated but let’s face it politics is what happens when groups of people get together and try to collaborate. There’s a lot of important work to be done around productivity economics and I’m glad it’s getting more mainstream coverage
> Productivity has a precise economic definition - ratio of output to inputs - and correlates highly to standard of living. We don’t fully understand how and why technology advances, but we measure increased technology through a variable called the solow residual.
What happens when you can't measure the outputs? What's the total value added by the financial sector? Or the legal sector for that matter? If I invent an inexpensive cure for a disease that renders expensive medicines obsolete, has productivity gone up or down?
Regarding the Solow residual, you certainly can put income on one side of a regression, and estimates of labour and capital on the other side, and set them equal using a residual term. I don't think you can convincingly argue to anyone besides an undergrad economist that the residual represents technology though. Don't think too hard about what the units of that residual are...
It’s an approximation that needs to be imputed, and can’t be measured directly. It doesn’t need units to be a useful measure against itself at different periods, to measure the rate of change of how environmental variables effect a nation or firms production function. I think it’s cool and useful that someone tried to quantify how much infrastructure affects productivity by abstracting away all the immeasurable variables into one term. It’s an extremely important concept that deserves more work because of how closely it is tied to advances in standard of living. It’s not perfect but it’s very interesting and could be ripe for a revamp given how much data we are now collecting from all sources
I could not disagree more strongly on this. First, objectively, we have no basis for saying whether or not the actions taken actually helped anything, because we have no control of any sort. All we have are theoretical models, which, I cannot stress enough, were absolutely useless in predicting the crisis in the first place, which, while not disproving their effectiveness, should at least give us pause. How many times can a model be wrong and "on-the-other-handed" before we admit that it is garbage?
Long-term it sounds like we're not in disagreement, but the short-term aspect I also find unconvincing. We still lost the jobs. People still fell down into debt spirals, specifically because the capital infusion allowed the banks to not reprice their mortgages, which is the only sensible way that they could have had any sort of business continuity; to take the write-down on the property values and allowing people to keep paying down the repriced debt rather than pushing things further down the cliff by forcing people to enter foreclosure and thus further depress the housing market.
Subjectively, we saved a couple of giant banks (and an insurance company) that collectively had taken on so much risk exposure that it dwarfed the total income that those institutions had made over their lifetime. Those were the institutions that most needed to go into receivership, to be broken into pieces and sold to smaller banks that had been more prudent with their investments. That process already existed in law and needed no special handling; Sheila Bair and the FDIC were ready and willing to do the right thing. Instead we end up with TARP and the ridiculous avoidance of actually relieving troubled assets, instead just giving a ton of money to the worst possible actors, and then fudging the balance sheet to look like we made a profit on the deal. The whole thing stinks and is morally repugnant and sets up all sorts of perverse incentives.
Okay, that's enough of the initial rant, and I apologize if it seems like I'm lashing out at your reply, which actually was well-balanced.
Productivity does have a precise economic definition, but it is not the colloquial one, and regardless, it is absolutely impossible to measure in any meaningful sense; all we can do is use statistical tricks with existing data to attempt to estimate it, but those estimators do not remain stable over time because the underlying metrics rarely have the longevity to serve back a few more years.
It's a rabbit hole I heartily recommend -- find an estimate of "productivity" and dig down to what it is actually measuring, and then see if those metrics can be compared to metrics from the past. If someone wants to take that on and reply to this, I'm happy to see the analysis; I haven't done it yet for this particular metric, but I've become familiar with the picture; colloquial term to "precise" economic definition, the methodology for estimating it as a point estimate based on other metrics whose provenance is dubious and which themselves have methodological issues that defy our ability to measure them over time (i.e. often devolving to self-reported data or tax data or labor that is subject to changes year over year; the changes in reporting requirements alone make the data useless). If we dug down and talked about the actual metric that we're talking about when we say "productivity" then it would be rapidly apparent that we're talking in circles.
Even more so, the methodology for most of this data has changed so much over time, with so little overlap between methodologies, that we have literally no idea what the state of the world was even a few years ago. All we have are a mixture of giant measurement artifacts, and when two of them correlate we celebrate because we might have found a metric that can bridge the divide between methodologies, but that correspondence disappears as soon as we try to find out if there are systemic changes -- our ability to determine whether something has changed has an implicit reliance on the assumption that nothing has changed, so all of these arguments become circular.
Econometrics is a philosophical dead end that just ends up producing broken policies disconnected from reality and causing us to make up a new suite of politically-motivated metrics to match the outcomes that we're looking for, and then give the metrics names that refer to things that have intuitive meanings and pretend we've found insight.
You really have to go back to non-econometric-based economics (the Austrians, von Mises and Hayek) to get any sort of insight into how economies can be made to work at scale, and the answer is that we don't understand them, and that technological progress and population changes mean that attempts to push them in a direction will have side effects that far outweigh any of the attempted influence.