Optimization: Dynamic Programming vs Kuhn-Tucker Considering the standard utility maximization of representative household which lives forever, one may use dynamic programming and Kuhn-Tucker in case of discrete time. For instance, one would like to solve,

max $\Sigma^∞_tU(C(t),N(t))$
 subject  to $P(t)C(t)+Q(t)B(t)<B(t−1)+W(t)N(t)+D(t)$

where $C(t)$ is consumption, $B$ is the bond, $Q$ is the bond price, $D(t)$ is a dividend, and $N(t)$ is the amount of labor.

Does the interpretation differ when one use Dynamic programming or Kuhn-Tucker?
Will it be something like this: In DP all the paths are optimized along t, but in Kuhn-Tucker only the path at time t is optimized.

If so, how you can make the above statement?

I would say that the main difference stems from the solution method, which results in your statement about all paths versus only the path at time t being true.

Dynamic programming (at least when done numerically) consists of backward induction. One tries to identify the optimal action for all possible values of the state variable in the final period, and then reasons backwards following the state equation. In this way one gets a solution not just for the path we're currently on, but also all other paths.

Similarly, if one uses the guess-and-verify method to solve the value function of the Bellman equation, the value function one guesses defines the optimal decision for all possible values of the state variable. Thus one gets a solution for all possible paths, including the current one.

Kuhn-Tucker basically works the other way around. One formulates the necessary and sufficient conditions, and solves the resulting difference equation(s) using the initial conditions as starting points.


Compound interest problem using PMT in Excel So I found this example in the net

  Compound interest formula (including principal):

  A = P(1+r/n)(nt)

  If an amount of $5,000 is deposited into a savings account at an annual interest rate of 5%, compounded monthly, the value of the investment after 10 years can be calculated as follows...

  P = 5000. r = 5/100 = 0.05 (decimal). n = 12. t = 10.

  If we plug those figures into the formula, we get:

  A = 5000 (1 + 0.05 / 12) ^ (12(10)) = 8235.05.

  So, the investment balance after 10 years is $8,235.05.

Okay, I'm using the PMT calculator in excel and I plug in these values

I get 53.03\$ per month, okay if I multiply it by 12*10 years I should get the same amount as the site, but now I get 6 363,93$

Why not the same? I use the pmt function in excel

The reason of this difference is that you do not fully understand what Compound interest is.

Actually, if you want to get the same amount as the site, while using your monthly payment, which is almost correct (more about this "almost" thereafter), what you must do is less straightforward than simply multiplying it by $120$ (calculation which would return the correct value in the $0$ interest rate case.)

What you must understand is that, the first monthly payment, let call it $P_0$, is going to capitalize (at a $\frac{5}{12}\%$ rate) for $120$ months, $P_1$ during $119$ months, $...$ and $P_{119}$ during $1$ month. And this is the sum of all these differently capitalized identical payments that you must compute to get $8235.05$.

That being said, if you do so, you will get $8263.36$ instead of $8235.05$, since the payment is actually due at the beginning of the period (whence the term almost above), i.e. you must set a $1$ instead of $0$ for the argument Type, which will return a monthly flow of $(\$52.81)$.

Thus, to summarize

$8235.05 = 52.8127046833568 \times \sum_{i=0}^{119} \left( 1+\frac{.05}{12} \right)^{120-i} \approx 52.813 \times 155.9292889
$

Where $155.9292889$ can be interpreted as an implicit capitalization factor.


How to compute Walrasian equilibrium in the case of logarithmic utility? If the utility is $U = \ln x + 2 \ln y$, how do you compute Walrasian equilibrium via usual formula for demand $x=a(x p_x + y p_y)/p_x(a+b)$ ?

What is $a$ and $b$?

In case of Cobb-Douglas function like $U=x^3y^4$ it would be simple: $a=3$ and $b=4$, but in this case how is it computed?

let $u \equiv xy^2$, then we have:
$$U=lnx+2lny=ln(xy^2)=ln(u)$$
Since $U'(u)>0 \: \forall u>0$ it follows that the $(x,y)$ that maximizes $U$ also maximizes $u$; $\max \{U\}=\max\{ln(u)\}=ln(\max\{u\})$. $u$ represents the same preferences as $U$.

Clearly, $u(x,y)=x^a y^b$ with $a=1$, $b=2$.


Why exchange rates of national currency are usually stable, where as cryptocurrency like bitcoin and ethereum is highly volatile? Exchange rate of national currency like US dollar or INR don't fluctuate much during a month or year, but the exchange rate of cryptocurrency like bitcoin is highly volatile even in a single day. What are the variables that impact the volatility of a currency? How does the government maintain the stability of its currency? Can one have a stable coin mathematically for example by changing the count of currency? How exchange rates of cryptocurrency and other currencies are calculated, who calculates it, what is math behind it?

The value of currencies (including most popular cryptocurrencies) is set by a market. If more people want to sell the currency (i.e., exchange it for a different currency) than to buy it then some of the sellers will be unable to find a buyer. Their only option will be to lower the price they demand until someone is willing to buy.

Likewise, if more people want to buy, say, euros than are willing to sell them then they will have to be willing to pay a bit more for the euros in order to persuade someone to sell.

In this way, price rises or falls until the supply and demand of the currency are equalised. So when the price fluctuates a lot, it is because either the supply or demand (or both) are changing a lot.

At the moment, cryptocurrencies have very little practical use. It's quite difficult to use them for many kinds of transaction. Thus, most of the trading of those currencies is driven by speculation: people buying and selling them in the hope of making money through changes in the price. This means the price can fall very rapidly when people think there is about the be a crash because everyone wants to sell to protect the value of their money. This is called a speculative bubble.

While euros (and dollars, and pounds,...) are sometimes used for speculation too, the main reason most people want euros is to buy stuff from/in Europe—whether that's German cars, or Bordeaux wine, or just stock in an Italian company. Likewise, the main reason people want to sell Euros is because they are Europeans who are trying to buy stuff made in America or China or elsewhere. They sell their Euros for dollars so that they can buy Ford cars or Coca Cola. In normal times the value of euros tends to be quite stable because the amount of stuff people buy from Europe and the amount of foreign-made stuff that Europeans buy doesn't change very quickly.


I there an established correlation between Federal Reserve balance sheet and MB( monetary base)? More precisely:
Are there any implied bounds for the ratio M0/FRBS with
MB= the monetary base
and
FRBS=Federal Reserve Balance Sheet?
https://www.federalreserve.gov/monetarypolicy/bst_recenttrends.htm
https://tradingeconomics.com/united-states/money-supply-m0

The two series are linked by an accounting identity, which is why they tend to move together closely. There’s no theoretical limit to how much larger assets can be than the monetary base, though. If you look at the two tables in the H.4.1 Release, you’ll see that the first table is basically the Fed’s assets (what you refer to as its “balance sheet,” but in reality one side of the balance sheet). The second table effectively shows the other side of the balance sheet, its liabilities. Two lines in the second table add up to the monetary base: “currency in circulation,” and “Reserve balances with Federal Reserve Banks.” The sum of all the other lines in the second table is the gap between the two series. These other balances serve a number of different purposes, and as of the moment I am answering this, the biggest contributor is something known as the Treasury General Account, which you can basically think of as the Treasury’s own checking account held directly at the Fed.


Does risk aversion of utility function cause the existence of positive interest rate? In standard macro model, it is usually time preference that causes positive interest rate. But is there anything to do with risk aversion of utility function that causes existence of positive interest rate?

Yes and no; it depends on which interest rate you look at.

You are right in that risk aversion affects interest rates, but the direction can go both ways. In what follows I look at an economy with risky (stochastic) and non risky assets and risk averse agents. For the thought experiment, we increase the volatility of the risky asset, "increasing its riskiness".

Risky Asset

Despite having the same expected return, due to Jensen's inequality, the risky asset gives less utility to the agents. The risky asset will need to pay a higher interest, a risk premium, to attract investors.

Safe Asset

We have increased the aggregate risk of the economy by making the stochastic asset more volatile. Agent's added utility from insurance (through safe assets) has increased. Demand for safe assets at the old interest increases. Holding the supply of safe assets fixed, this means that the safe asset's interest rate will go down.

To understand this fully, you might want to write down a two period model with two different assets, one standard normal with standard deviation $\sigma$ and one deterministic. Examine how interest rates for both assets change if you increase $\sigma$.


A weaker definition of local non-satiation can also imply indifference "curve" Let $u$ be a continuous utility function on $\mathbb R^2_+\setminus\{0\}$. Consider the following three conditions:

Local non satiation says that for any $x \in X$ and $\epsilon > 0$, there exists $y \in X$ such that $d(x,y) < \epsilon$ and $U(x) < U(y)$.
Local non satiation* says that for any $x \in X$ and $\epsilon > 0$, there exists $y \in X$ such that $d(x,y) < \epsilon$ and $U(x) \neq U(y)$.
The indifference sets of $U$ are curves.

As a standard result, (1) implies (3) and (3) implies(1).

Obviously, (1) implies (2) so (3) also implies (2).

Can (2) also imply (1) and (3)？

(2) does not imply (1). Consider a utility function with "circular indifference curves", e.g. $u(x,y)=-(x-1)^2-(y-1)^2$. At the bliss point $(1,1)$, the function satisfies (2) but violates (1).

(2) does imply (3), and the proof should be similar to the one showing that (1) implies (3).


Text book for mathematical economics? I need a text book for mathematical economics with real world examples. Currently I'm using A.C Chiang (very good) and Henderson and Quandt ( not the best book for matheco). Can someone recommend any others ?

Chiang is probably the best you can find, but you might try Takayama - Mathematical Economics or Simon and Blume - Mathematics for Economists.


Crude oil price changing factors I tried to summarize my thoughts about oil price changes, and try to understand the next weeks.

Will decrease price:

OPEC output is higher every month, increasing supply.
interest rates goes up, will reduce demand, less cars, less depending, less companies.

Will increase price:

Canada production outage
inflation, causing goods price to be increased
fracking extracting is costly, which is sensitive to interest rates, higher rates will cause less fracking, less supply.

I'm trying to understand to increasing factors, that released the price from 50-60\$ area into above 70\$ area.

Does anyone have ideas for why we are at high levels right now (and it looks like we will get higher)?

Thanks

Why have prices gone up?

Because supply was less than demand. The price has now increased, to bring supplies onto market, and to reduce demand.

Will it go higher? No one knows. The market thinks not, otherwise prices would already have gone higher.


Why does the price for a prescription drug fluctuate? "In drug price hearing, Congress tries to answer some basic questions" - dateline June 2017 CNBC.

I order a brand name prescription that has no generic, that is still under patent protection, that is not an orphan drug from a large mail order pharmacy. I have been getting this same prescription for six years. The mail order firm buys direct from the manufaturer, adding their overhead and profit to the price and then is paid by (1) my direct payment and (2) payment from my drug prescription insurer.

Over the past two years (in particular) the sum of payments (from 1 and 2 above) to the mail order pharmacy has varied substantially, and inconsistently (eg. increases and decreases) from a low of \$1400 to a high of \$2600 for the same 90 day order.

To be more specific in my question, why would a manufacturer price for a drug fluctuate as I describe.

One area That I've not been able to research is if Insurances companies negotiate pricing with the manufacturer -- but if that is the significant factor -- it suggests that the negotiated pricing only holds for 90 days or so.

Any insight would be helpful.

If their is a better place to ask this question, please suggest.

Prescription drug prices, like those of most other retail products, fail to satisfy the law of one price routinely. The most obvious observation is that prices differ across pharmacies at a given point in time (http://www.nber.org/papers/w8548.pdf) but just like supermarkets give discounts, so do pharmacies. If you always buy from the same shop, you are bound to end up paying different amounts.

The reasons for this are manifold. Different consumers have different abilities or willingness to store and buy large chunks when it is cheap and stochastic prices allows for price discrimination (see Sobel 84 for an early reference). The idea is simple. Myopic consumers arrive in each period and buy if $p<V$, then leave the market. Otherwise, they die. Strategic consumers have a valuation of $v<V$ but can wait if the price is above $v$. Firms compete in prices. In equilibrium, firms charge often $p=V$ to extract rents from myopic consumers but every now and then they offer $p<v$ to attract all strategic consumers looking for prices.

Competition between stores may also result in random prices in a standard consumer search framework. Finally, retail prices may change because manufacturers prices are also random as a way to discipline pharmacies by encouraging consumers to shop.


What are exactly considered resources in modern economics? I'm taking a basic course in economics and I'm trying to understand what the term "resources" really mean in this context.
Reading this article, I found out that in classical economics, resources are usually divided in 3 categories: Land, Labour and Capital.
Anyway, while watching some videos, often I see enterpreneurs as another possibile type of resource.
Now, is this an addition of modern/present economics?

**I've seen that often "modern" and "classical" economics are interchangable attributes referring to the same thing: the view of economics started with the works of Adam Smith

What I think you want to consider to be grouped with land, labour and capital is another factor to be considered with labor- technology (A.K.A "Knowledge*).

The term "technology" here means an augmenting factor which is external to the present amount of labour. This can mean improved machinery to produce goods and services or alternatively, this can be viewed as a improvement in human capital which is what training employees can be viewed as in terms of technology.

For more information about the effect of technology/improved human capital in economics, I would recommend checking out the Solow Model and the Skill premium Model

Hope this is helpful!


Max of a profit function: partial derivative of an integral function? I am struggling with the maximization of the following profit function in a New-Keynesian model. Here there is the FOC.
$$\frac{\delta}{\delta Y_t(i)} P_tY_t- \int_0^1 P_t(i)Y_t(i)di = \frac{\delta}{\delta Y_t(i)} P_t\left[\int_0^1 {Y_t(i)}^{\frac{\epsilon-1}{\epsilon}} di\right]^{\frac{\epsilon}{\epsilon-1}} - \int_0^1 P_t(i)Y_t(i)di = 0 $$
$Y_t(i)$ is the demand for the intermediate good and $Y_t$ is the demand for the final good. The solution should be:
$$ \frac{\epsilon}{\epsilon -1}  P_t \frac{Y_t}{Y_t^\frac{\epsilon -1}{\epsilon}} \frac{\epsilon -1}{\epsilon} Y_t(i)^{-\frac{1}{\epsilon}} = P_t(i) $$
I tried to apply the Leibniz integral rule. However, I cannot understand how to behave when taking a derivative of an integral function.
May anyone explain to me the steps (and the mathematical theory) in order to get the correct solution?
Thank you in advance for your patience and your support.

You are really asking about the marginal product of a CES production function.
The LHS of your second equation is $P * dY/dY(i)$ where $Y_t$ is a CES aggregator of the $Y_t(i)$.
Let's define $\rho = \frac{\epsilon-1}{\epsilon}$ so that $Y=[\int Y(i)^\rho]^ {\frac{1}{\rho}}$.
Now apply the chain rule to get the derivative (also available for lookup in any micro text book):
$\partial Y/\partial Y(i) = \frac{1}{\rho} (\int Y(i) di) ^ \left(\frac{1}{\rho}-1\right) \rho Y(i)^{(\rho-1)}$
Cancel a few terms and you have your answer.


How are PPP, nominal exchange rates and inflation related? This Forbes article discusses how changes in the market exchange rate can be used to estimate an inflation rate thanks to the principle of purchasing power parity (PPP).

Can someone distill this process a little better? I can follow the steps mentioned in the article, but the underlying principles are still not clear to me.

Let $P$ denote the price in the home country, $E$ represent units
of domestic currency used to buy one unit of foreign currency, and
$P^{*}$ represent the price level in the foreign country. Now, PPP
implies that:
$$
P=EP^{*}
$$
 In other words, prices when expressed in the same currency are equalized
across countries. Log-differentiate and take changes and obtain:
$$
\hat{P}=\hat{E}+\hat{P}^{*}
$$
 where hats denote changes. Rearrange, and find that:
$$
\hat{E}=\hat{P}-\hat{P}^{*}
$$
In other words, the changes in exchange rate inform one of relative changes
in price levels (inflation). This is what is know as relative PPP


Is it true that when the overall money supply decreases, that the demand for money decreases and the demand for bonds and securities both increase? Is it true that when the overall money supply decreases, that the demand for money decreases and the demand for bonds and securities both increase?

I understand that to increase the money supply, the central bank uses cash reserves to pay for bonds. I’ve been thinking about this for a while, but does this lead to an increase in demand for the bonds and a decrease in demand for money or is it the other way around?

The quantity of money supplied has nothing to do with either the demand function of money or the demand function for bonds.

If there are changes in monetary policy such that the quantity of money supplied in equilibrium changes, then the quantity of money supplied clearly increases. In most models it is assumed that demand for money is decreasing in the nominal interest rate, so one way to achieve an increase in demand for money is to decrease the nominal interest rate. As people will hold more of their wealth in money, they will hold less in bonds.


A question from MWG 2F12 This question is from MWG
if walrasian demand function is generated by a rational preference relation then it must satisfy weak axiom.
I cannot prove this statement. How can I do?Thanks alot.

"If the new bundle was affordable at old prices, and the new and old bundles aren't equal, then the old bundle must not be affordable at the new prices".
In other words, the Weak Axiom of Revealed Preference (WARP) refers to consistent (rational) decision-making.
I think the proof is in terms of an 'if then' direct method:
The Marshallian demand function $x(p,w)$ satisfies WARP if the following property holds for any two price-wealth situations $(p,w)$ and $(p',w')$.
If $p*x(p',w')\leq w$ and $x(p,w)\neq x(p',w')$ then: $p'*x(p,w)>w'$.


Which institution (government or private) provides the complete data on HS (Harmonized System Code), tariff schedules for India, China and US? Was looking out for options on building a data store having HS code and tariff schedule data for few countries, which I can use as a base for import calculations and general HS lookup.

Is there a government or private body (specifically for the countries US, China and India) from which I can source this data in a digital format, which of course I may further process according to my storage model.

Just a note: I'm aware that there already exist websites and applications which provide cost calculations services as limited free and on chargeable terms.

The best place for this information is WTO TAO. The data does require a little cleaning but you have information on a countries' mfn


Gali - Monetary Policy - Solutions? I am working through exercises in Gali but some of them are rather difficult. I am trying to find a solutions manual to use as an aide for exercises that completely stump me and to confirm solutions for the exercises I have completed.

Does anyone here know if Gali or some other economists published solutions for his exercises?  I have searched extensively with no luck but it seems like there must be some sort of solutions manual available for this text. It is widely used.
Thanks

I don't believe that a solution manual to Gali's book has been written. In 2015 the book saw a second edition, so maybe this time around something will appear.
These course notes may be indirectly helpful to you.


There is a paragraph about the history of credit rating agencies that I don't understand "For a few decades, ratings were nothing more than private assessments, no different from any other form of consultancy provided to investors.
Born out of a need in the burgeoning industrial world of the late nineteenth century, the power of credit agencies increased with the shift affecting the financial industry in the interwar period, especially the banking sector.

Traditionally, banks had been the primary source of funding for firms and corporations. They were the link between lenders (mostly private savings, i.e. deposits) and borrowers.
Credit defaults (and the risk thereof) were shouldered by them and usually did not affect depositors.
Therefore banks ‘acted as hybrid institutions of collective action, between the state and the market’, controlling the risk and reducing ‘the uncertainties for the political authorities, as well as for borrowers and lenders’.

Yet the increased downward pressure on capital costs experienced during and after the Great Depression incentivized direct market participation for banks (in form of financial and investment products) and eventually decreased their role as mediators between lenders and borrowers.

As a result, such ‘disintermediation’ transformed banks from agents of self-regulation to market participants.
The decentralization of capital allocation (away from banks), directly connecting borrowers and lenders, accentuated the problem of asymmetrical information in the market and thereby strengthened the role of rating agencies."

What does "decreased their role as mediators between lenders and borrowers " mean when it is already said that "credit defaults (and the risk thereof) were shouldered by them(banks) and usually did not affect depositors."
What does "the increased downward pressure on capital costs* experienced during and after the Great Depression incentivized direct market participation for banks" mean?
That cheap credit turn banks into investment firms?
What does the "the decentralization of capital allocation (away from banks)" mean?
I think it means that the now investment firms, formerly banks are now trying to sell people bad performing stock on their books, while their consumers are trying to get loans ?

It’s an extremely long-winded way of saying that lending moving from bank lending to bond/money markets. The fact that depositors did not take much direct credit risk is a red herring.
I don’t see the financial logic, but yes, the banking sector moved from being lenders to underwriters of securities.
Bond and money markets are decentralised: instead of a single bank making a loan, there is a group of investors buying a new bond or money market instrument.

The passage is inherently confusing, as it is based on a couple of questionable premises.


Comparing & contrasting decision problems and normal games I am trying to compare and contrast between decision problems and normal games. Are there any key concepts I should know? Any help would be greatly appreciated.

Decision under uncertainty is sometimes called a "game against chance", and can thus be modeled as a two-player normal form game: the decision-maker vs Nature/Chance. The possible states would form a set of pure strategies for Nature, and Nature commits to a publicly known mixed strategy that randomizes over those pure strategies (assume Nature is indifferent between all outcomes so that the mixed strategy is rational). The decision-maker's best response to this known mixed strategy is equivalent to the choice that maximizes his expected utility in the decision problem. In this sense, decision problems are really just a special case of a game.
The above suggests that your statement

A decision problem deals with expected utility, whereas normal form games do not.

is incorrect, since normal form games do deal with expected utility, especially when proper mixed strategies are involved.


Use of mathematics and imprecise definition of terms As a postgraduate student of economics I've been trying to expand my mathematical "toolset". While doing so I've talked to engineers, physicists and mathematicians, many of which have disdained the use of mathematics in economics. Their arguments vary, but one common theme is summed up by mathematician Michael Edesess' critique:

Economics pretends to be mathematics, but it is not mathematics. There
is a major difference. No mathematician uses a term in a formula, or a
statement of a theorem, unless that term has first been defined with
excruciating precision.
And while economists may think they’ve defined terms like "aggregate
demand" or "economic growth", they should try reading some real
mathematics to see what a precise definition truly is. The economists,
I think, leave the work of definition to be inferred from the way the
terms are used in the formulas.

I believe I know the precise definition of (quite a few) economic terms, but maybe Edesess is pointing out to some more profound mathematical foundations which I may not be familiar. Could someone expand on his argument and maybe even counter back?

Edesess is attacking what is really just a straw man of economics. I'm not sure he really understands the field. To start, economics is not math. We're not claiming that it is. It's more of an "applied" science. Economists have never claimed that these definitions are precise in the way that mathematics is. These definitions are modeling constructs---they're for applied work. They're use is temporary in a way. The point is to try to convey an idea in a more precise way than just in words---but everyone knows that they're not a precise as we would like and not as precise as they ultimately should be. They're meant to be debated and later refined. But, as all applied scientists know, you've got to start somewhere and sometimes ideas are best conveyed through simpler---if less detailed mean.

Coming up with better definitions is a huge part of the economic science. Consider these examples. When the Cowles Foundation was founded in 1932 its motto was "Theory and Measurement" (the motto was first adopted in 1952). Measurement is not an easy thing to do. As another example, a lot of Larry Kotlikoff's work has dealt with how a lot of fiscal measures are not economically well-defined concepts.

  Einstein taught us that neither time, nor distance are well-defined physical concepts. Instead, their measurement is relative to our frame of reference – how fast we were traveling in the universe and in what direction. Our physical frame of reference can be viewed as our language or labeling convention. ... Kotlikoff, along with Harvard's Jerry Green, offered a general proof of the proposition that deficits and a number of other conventional fiscal measures are, economically speaking, content-free, concluding that the deficit is simply an arbitrary figment of language in all economic models involving rational agents.

Also, take another example of current interest. Lars Hansen's recent work (winner of the 2013 Economics "Nobel" prize) has focused on the difficulty and ongoing failure to define certain economic concepts, including "bubbles" and systemic risk. See his essay "Challenges in Identifying and Measuring Systemic Risk". I'm a fan of the dictum he relays, attributed to Lord Kelvin,

  I often say that when you can measure something that you are speaking about,
  express it in numbers, you know something about it; but when you cannot
  measure it, when you cannot express it in numbers, your knowledge is of the
  meagre and unsatisfactory kind: it may be the beginning of knowledge, but you
  have scarcely, in your thoughts advanced to the stage of science, whatever the
  matter might be.

He notes that "an abbreviated version appears on the Social
Science Research building at the University of Chicago." So, yeah, economists (as social scientists) definitely take this seriously.

So, the point is that economists are well aware of the problems in these "definitions." They are a part of ongoing research in the field; sometimes they're ignored if people don't think they're first-order to the problem; etc...


Why is UK infrastructure so expensive? Current official estimates for the proposed UK railway line High Speed 2 are £42.6 billion for a 192 km line, or around £222 million (€287 million) per km (if my calculations are correct).  A 2020 review suggests it could even cost as much as £106 billion (€126 billion), or £552 million (€656 million) per km.

The French LGV Est total cost is around €4 billion for around 300 km, or €13 million per km — a factor 22 less than the initial UK price or a factor 50 less than the 2020 high estimate.

The German Nürnberg-Erfurt high speed railway line total cost is estimated at around €5.1 billion for 190 km, or around €27 million per km — a factor 10 less than the initial UK price or a factor 24 less than the updated price.

The Swedish planned Östlänken line is estimated to cost around 30 billion SEK (€3.2 billion) for 150 km, or around €21 million per km.

The French, German, and Swedish high speed railways are all in a range of 10–30 million €/km.  Why is the cost for the UK High Speed 2 a factor 10–50 higher?  What makes it so expensive?

The costs for a third runway at Heathrow Airport are estimated to be £18.6 billion £32 billionsource.  For comparison, the 2003 Polderbaan was €320 million, which is far less even when taking into account inflation.  Quoting the Financial Times:

  While an additional runway would indeed seem desirable, it would not be worth paying such exorbitant costs. Why such projects are so expensive and so difficult to implement in the UK is, to me, the big puzzle. It cannot just be because southern England is densely populated. So is north Holland, where Schiphol, with far more runways than Heathrow, is located.

The following information comes from this report, which was published by the British Government.

I'm not going to summarise the whole thing, but go over the major points. However if you are interested in the topic I suggest you read the whole thing, or even take a look at the more technical version which can be found here.

The report breaks down the higher costs into three issues:

Policy and systemic issues
Funder/client issues
Supply chain delivery issues

Policy and Systemic Issues:

Urban Density: The report indicates that high urban density coupled with high land costs has driven up the price of infrastructure in the UK, however it says that it does not adequately explain the whole problem.
Planning and consultation process: Inconsistency between how planning works with different areas of the country as well as general constrains placed on the early planning process has been marked as a key driver of higher costs in the UK than Europe.
Regulatory Compliance: The report indicates that high environmental and safety regulation has led to what some contractors call "not cost effective". However the report also mentions that the UK has the best safety record in Europe. So it would be a tradeoff to lose such regulations.
Wider construction market issues: The UK has the smallest construction market of the big five countries in Europe which has seen a shift from fixed to variable resources. This means there are less firms investing in construction which leads to higher levels of subcontracting and supply chain specialisation. The report argues that this leads to higher transaction costs along the supply chains.

Funder and Client Issues:

Stop and start investment: The report makes a very interesting argument here whereby it says that the UK's short term investment plan compared to Germany and Frances long term investment plans, allows the latter countries to reduce costs. This is because it allows for opportunity for innovation and the ability to plan work more efficiently. As well as the fact that it generates investor certainty as the projects are more long term.
Poor governance and ineffective incentivisation of cost control: The report argues that the tender process is not focused on cost minimization and there are not enough ways to incentivise it. As most projects work through a quoted budget as opposed to aiming for the lowest cost for a required peformance.
Poor asset information and cost data: The report argues that lack of information about infrustructure costs makes for poor descion making.
Commercial issues and procurement processes: The UK relies heavily on bespoke specifications and contracts, where out of the box solutions would often suffice. Many western european countries have the nature of these contracts codified in law, whereas the UK doesn't.
Insurance: More expensive in the UK

Supply chain delivery issues

There is poor supply chain integration in the UK
There is high fragmentation among construction industries in the UK leading to inefficincies
Large skills gap
Lower productivity

tl;dr

  "There is no single overriding factor driving higher costs. However,
  the investigation has identified that higher costs are mainly
  generated in the early project formulation and pre-construction phase"


What's the difference between Quantitative Easing and regular central bank operations? Most articles describe QE as purchasing government securities on the market.  I thought that was what ordinary day to day operations of the central bank were in their efforts to maintain a target interest rate.  So if they aren't buying government securities day to day, what is it they do to manage the bank lending rate?

In usual open market operations, the central bank will create money, use this money to buy short term Treasury securities from maybe banks, individuals, institutions in the open market. This creates more demand for these securities. Hence their price goes up and yield goes down. This newly generated money goes into the banking system. With more money, banks have more cash and have more reserves. With more reserves banks may be more willing to lend to each other and to individuals also. This lowers the short term inter banking interest rate. This way, there is more money in the system and there is a downward pressure on rates. With short term Treasuries, central bank is less exposed to the interest rate risk.

In quantitative easing (QE), both the purpose and the mechanism are different. First of all, QE usually will be performed in a situation which is not 'typical' money supply shortage or economic activity slowdown. This will either happen in a crisis where aggressive boost is required or when central bank has run out of its primary weapons. Maybe it already lowered interest rates to zero.   The central bank in these situations might buy securities of different kinds which can be long term treasuries, private securities, securities in a particular area of market which, the central bank thinks, needs to be revived. This certainly will not just increase money into the system, but further lower the yield and ease out specific markets such as mortgage based securities by reducing the risk spread.

One other criterion is the size of the increase in balance sheet of central bank. In QE there is usually a much larger change in the balance sheet of central bank. Also, as there are different kinds of securities (including long term securities) in the assets of central bank which are not necessarily treasuries or highly rated securities, the central bank itself is exposed to more risk.

Ben Bernanke said in 2009 that, the QE they exercised was not pure QE but credit easing, because in pure QE, the central bank will not discriminate between what securities it is buying. However, according to him, Fed did target few specific markets. Targeting few specific markets is more like credit easing and not pure QE.


Can all the regressors be endogenous in a given model? I'm trying to estimate the following model:
Labor demand=f(wages,lagged labor demand, GFCF, GDP, trade share, labor productivity, real exchange rate)... (1)
Wages= f(labor demand,lagged wages, GFCF, GDP, trade share, labor productivity, real exchange rate)...(2)

When i run endogeneity test in stata and dumitrescu hurlin test in Eviews, they say that all regressors are endogenous. Is this something normal or I'm doing something wrong?
Eagerly waiting for a reply.

In principle, there is nothing to exclude the case where all regressors are endogenous.

My issue is that the Hurlin-Dumitrescu test has to do with Granger-causality, and Granger-causality examines the relation between the regressors and the dependent variable, not the relation between the regressors and the error term. On the other hand, endogeneity refers to the existence of correlation of the regressors with the error term.

So it appears that the Hurlin-Dumitrescu test is of no use on testing for endogeneity. Do I miss something here?


How can the replacement level fertility be 2.1 everywhere in the world? Common sense would indicate that the replacement level fertility of Norway ought to be lower than that of Sudan due to fewer children dying there. Why, then, is the replacement fertility rate universally taken as 2.1?

Your claim that the replacement level fertility is "universally taken as 2.1" is false.

World Resources Institute:

  This rate is roughly 2.1 children per woman for most countries, although it may modestly vary with mortality rates.

Craig (1994):

  In developed countries, replacement level fertility can be taken as requiring an average of 2.1 children per woman. In countries with high infant and child mortality rates, however, the average number of births may need to be much higher.

2.1 is simply a very crude and made-up figure. It's just 2 (replace the parents) plus a little more (arbitrarily assumed to be 0.1) to account for mortality.

Where a writer is unable or unwilling to obtain better estimates, she will often simply use this 2.1 figure. But this does not mean she believes that the true replacement level fertility in her context is precisely 2.1.


Oaxaca decomposition - Interpretation Interaction I am running a Oaxaca decomposition on trends in paid work (similar to this paper)
The estimates are expressed in minutes.

The total change shows an increase in about 30 minutes between Period 0 and Period 1.
I have some difficulties to understand what the Interaction means here. So the Endowments represent the observed characteristics of my model and the Coefficients the unobserved.

What about the Interaction? How should interpret the fact that it is negative ?

                     Decomposition
Period 0                   174.66
Period 1                   204.15
Total Change               29.5
.
Endowments                  22.78
Coefficients                50.38
Interaction                -43.66

In principle the idea is that there are three sources of the 29.5 change:

Lets assume we are taking period 1 as the 'baseline'. The first source of the 29.5 change is that the independent variables changed. To see the importance of this effect, you estimate education's effect on time for period 1. Then you apply the estimated model to the period 2 education and you get a predicted increase in time because the period 2 were more educated on average and the model predicts that higher education leads to more time. Suppose that estimate amounts to 22.78 minutes in this case.

The second source of difference is found by estimating the model with period 2 data. Then you look at the different coefficients on education from the period 1 and period 2 models and apply the difference to the period 1 data. In other words, you see how much the function changed, as measured for the period 1 education levels. Suppose that in the second period, the effect of education seems to be larger. This difference in the coefficients explains 50.38 minutes of the difference between 1 and 2.

Finally to interpret the interaction term, you have to imagine that you apply the difference in the models to the difference in the data. While the period 1 education using the period 2 model implies a high time and the period 1 model applied to period 2 education also implies a high time, it turns out that the period 2 model applied to the period 2 education yields a small time. This idea that when you interact the period 2 data with the period 2 model you get a different result than if you had just summed up the education change by the period 1 model and the model change by the period 1 data is what is at stake. In this case it turns out that the combination in yields a lower value than what is predicted by the sum of the differences. The interaction term is then difference between what you expected from the two individual differences and the result. In this case its a negative number, -43.66.

Another way to see this is to imagine we are decomposing the difference between f(x1,x2) and f(x2,y2). As you go from x1,y1 to x2,y2, you will advance over the x axis. You expect the function to change Dx=(x2-x1)*df/dx(x1,y1).AS you go from x1,1 to x1,y2 you will advance over the y axis. You expect the function to change Dy=(y2-y1) *df/dy(x1,x2). Lastly you compare your results and realize that there's an error, xi, so that f(x2,y2)=f(x1,y1)+ Dx+Dy +xi. Dx here corresponds to the endowments effect, Dy to the coefficients effect, and xi to the interaction effect.


Is there a statistic that shows which countries would be owed money if all external public debts were payed immediately? The media loves to tout big debt figures whenever there is an economic crisis, but unless we know who owes money to who, it seems to me that these figures are useless since debt is all relative.  I know that economic policies are changing all the time, so the figures could shift, and that different states are paying their public debts at different interest rates. Therefore, looking at what I will call "collapsed external debt" is a gross oversimplification- but nonetheless I think this would be a useful heuristic figure when seeing who comes out on top today after all is said and done(although that would never actually happen).

If this figure does not exist or would not be useful in any way, then why not?

The description given implies to me that you want to net the debt holdings between governments only. For example, we would subtract the Chinese government's holdings of U.S. Treasury securities from Chinese debt (and so forth).

I am unaware of any such statistics. For the developed countries, the amount of cross-governmental debt holdings is minimal (excluding the ambiguous situation of the European Central Bank). Therefore, such an adjustment would only matter for some developed countries. (The ratio of governmental debt to reserves - which are holdings of developed country debt - is probably looked at by ratings agencies and analysts of developing countries.)

A more usual statistic is the net international position, which compares national holdings of foreign assets versus foreign holding of domestic assets. However, this mixes all form of financial assets (debt and equity) and includes both the private sector. The IMF has a standard for reporting the international investment position - link to page

The usefulness of such statistics enters the realm of opinion. The main usage of the net international position seems to be the assessment of the odds of a currency crisis; I am unaware of the literature on that subject.

As for debt statistics, things like the debt-to-GDP ratio have been greatly discussed. However, I am in the camp that argues that the main "use" of debt statistics has been to generate incorrect forecasts (such as the sustainability of Japanese debt). In general, the link between debt levels and bond yields for the developed countries is questionable, which indicates that bond investors are not greatly impressed by the importance of debt statistics.


Macroeconomic formulas for global limited raw material economy exist? Macroeconomics basic formulas are referring to a model in which the raw material are unlimited.
Also the efficiency of production is a consequence of the pressure done by consumers (that buy the most cheap product, between the ones with the same level of quality).

exist formulas that try to model an economic system that "expand" toward the maximization of efficiency in using the limited quantity of raw resources?

(provided that we can describe the actual basic model like one that "expand" toward the maximization of quantity of production and quantity of selling, by total units or by total revenue).

I am not an expert on the domain. However, a popular extension in various domains of macroeconomics is to replace the standard Cobb-Douglas function

$$Y=AK^{\alpha}L^{1-\alpha}$$

by a production function that take a third resources (typically called land and noted $T$) which is supposed to be in a constant quantity. The production function hence becomes

$$Y=AK^{\alpha}L^{\beta}T^{1-\alpha-\beta}$$

With

$$\frac{\dot{A}}{A}=g $$
$$\frac{\dot{L}}{L}=n $$
$$ \dot{K}=sY-\delta K $$
$$\frac{\dot{T}}{T}=0 $$

It is -to my knowledge, typically used in growth theory, to account for malthusian theories, more here for instance, and some empirics Here, but i guess every textbook in growth has a note or more on it.

I also recall seeing it  in international trade, but less frequently.


Relative risk aversion, a property of period or lifetime utility This question is to be understood in the context of consumption based asset pricing.

I'm wondering whether relative risk aversion is a property of the period utility function, which is simply a function of a specific $c_t$ such as a power utility function $u(c)=c^{1-\gamma}/1-\gamma$, or if it is a property of the total / lifetime utility function, which is defined as a function over a consumption plan ($c_t$, $c_{t+1}$, ...), e.g. as an additive model over two periods $U(c_t)=u(c_t) + \beta E_t[u(c_{t+1})]$.

In this standard additive utility framework with e.g. the aforementioned CRRA power utility, this does not seem to make a difference as both would lead to $\gamma$ being the RRA.

However, it is less obvious in a recursive framework such as Epstein-Zin-Weil, as I'm not sure how the period utility function $u(c_t)$ would even look like.

Any help is greatly appreciated.

Though this probably doesn't fully answer your question, given that it's been active for a little while with no other responses, this might hopefully be able to give some direction.

First, it's important to note that the Arrow-Pratt measures of risk aversion are just one possible measure of risk aversion. While it certainly has nice properties in many set-ups, if, for example, the agent doesn't follow expected utility theory, then the Arrow Pratt measure loses it's explanatory value.

When it comes to intertemporal risk aversion, it's generally worthwhile to consider risk aversion to be "how much an agent, in period $t$ would be willing to pay to avoid a particular gamble in period $t+1$?" For this, there seem to be several different derivations of measures of risk aversion, depending on the specific assumptions made about the within-period and between period utility function. Given that you've mentioned Epstein Zin, it's probably worth pointing out that their 1989 paper's focus was on divorcing intertemporal elasticity of substitution from risk preferences, and they take 15 or so pages to go through what risk aversion means in their non-separable framework, and how to define it. Perhaps more helpful is this recent work that considers a relatively general definition of risk aversion in a multi-period macro context, which can include some recursive inter-temporal aspects of utility. This paper also considers a model with non-additively separable utility, and shows that the CRRA coefficient is still the same as it is in the additively separable case. This might be another interesting paper since it also considers risk aversion over a planning horizon without separability.

That said, as this small set of lecture notes shows, if you're primarily interested in measures of RRA using a traditional measure, define it at period $t$ by taking the overall utility function's derivatives at the period of interest. There might be some non $t$ period consumption variables in that measure, but that's fine. This set also points out the interplay between risk aversion parameters and intertemporal substitution parameters.

If I find more I'll edit this response, but hopefully this provides at least a good start!!


Is it possible for shareholders to get a companies assets in place of currency? To my knowledge being a shareholder is owning a portion of a company. Then by that logic shouldn't a shareholder be able to request a companies assets instead of money? As an example, if I own 100 dollars worth of shares in XYZ company would I be able to get 100 dollars worth of their assets (chairs, tables, laptops)?

The short answer is no.

Even on a liquidation scenario it’s unlikely that a common stock shareholder would be distributed physical assets.

Assuming this is a C-Corporation you are asking about, shareholders do not have rights to ‘money’ or assets held inside the company- If the shares are of a preferred class with dividend rights you may receive a portion of retained earnings.


Education Spending Ratio Oscar Tabarez, the current football manager of Uruguay National Team, have urged, after his good results, his governement to raise, as promised, the Education Spending on GDP Ratio to 6%.

It is a very good resolution indeed and it makes me looking how my country, France, is ranked.
Someone, could help to understand why France (i'm french) has a low level in comparison with Mexico, Brazil or Argentina and is one of the last country of OECD.

source : https://data.oecd.org/eduresource/education-spending.htm

Are we more efficient with Public Expenditure ?

It is large issue but any comments will help me.

My work focuses on the Economics of Education, although from a more micro perspective. I can honestly say it's a complicated question and there are many people working on optimal education spending.

First, a bit of simple math. Let $EdExp$ be education expenditure, $GDP$ be Gross Domestic Product, $E_{students}$ be enrolled students, $S_{pop}$ be school-age population, $N_{pop}$ be non-school age population. One can decompose Education Expenditure by GDP ratio in this way:

$$ \frac{EdExp}{GDP} \equiv \frac{E_{students}}{S_{pop}} \times \frac{S_{pop}}{(S_{pop}+N_{pop})} \times (\frac{EdExp}{E_{students}} \times \frac{(S_{pop}+N_{pop})}{GDP})$$

Note this isn't a "made-up formula", it's an accounting identity. This is true in the US, China and in a tribe of herdsmen. I'll translate its terms to english. $\frac{EdExp}{GDP}$ is Education Spending to GDP ratio, which Tabarez thinks should be 6%. $\frac{E_{students}}{S_{pop}}$ is the enrollment rate, the fraction of people who are school-aged and attend school. $\frac{S_{pop}}{(S_{pop}+N_{pop})}$ is the dependency ratio, the fraction of the population that is school aged. Lastly, $\frac{EdExp}{E_{students}} \times \frac{(S_{pop}+N_{pop})}{GDP}$ is education expenditure per student divided by GDP per capita. This is the proportion of average income that is spent on the average student.

Countries like France have high GDP per capita and low dependency ratios, which means they can sustain high expenditure per student without having to compromise a large share of GDP on education. Uruguay and Brazil, on the other hand, have high dependency ratios and somewhat low GDP per capita. Enrollment rate isn't very high too. So, in order for these countries to sustain high expenditure per student (which is what ultimately counts), they need to reserve a larger share of GDP for education.

That's one part, the one having to do with demography and aggregate spending. I'd like to talk about the one some of my research is concerned with, spending efficiency. Uruguay is not an extreme case as Brazil, but it shares many problems with its northern neighbor.

Out of the ~6.5% of GDP that Brazil spends in education, only about 1% goes to public fundamental/elementary schools. About 1% goes to public high schools and the rest goes to public universities. This is just terrible. You can't spend 2% of GDP on dozens of millions of students and then 4% on 1 million of them and expect the first system to have reasonable quality. Then, we have the institutional problems. In most states, schools aren't allowed to pay bonuses to better teachers and many poor municipalities can't even hire trained teachers because of low pay, depending on self-taught locals to teach. Access to federal resources such as financing for new materials and data to better understand your school's demands is somewhat easy but mostly untrained, unqualified school managers don't know what to do with these resources.

In the cities and school that do have somewhat qualified personel and more money, public tenure rules in Brazil make it impossible to fire low productivity teachers and managers and even promote the good ones. Leading to overall lack of incentives.

On one hand, spending matters. It's hard to imagine schools giving good education if there aren't blackbords, chairs and basic equipment in it. On the other hand, poor institutional design and lack of incentives can make tons of money go to waste.

As a rule of thumb, anything in the 4-5% education spending to GDP ratio is reasonable. More than that means mostly resources going to waste if there aren't serious attempts to create better incentives and improve school management.


Trade cost on Endowment model I think in real endowment model, if there's trade cost as 't', then the MRS should be really small or large to make a consumer trade his endowment goods. Is there any model include this trade cost or market tax?

If it's true I think we can examine how much 't' can make a consumer not to use market and that can bring decrease in market exchange. So government can focus on decreasing 't' to the level of free trade(technological or even the number of markets).

You can easily think of an endowment economy with taxes, and think of the taxes as transaction costs or trading costs. I'm sure classic textbooks like Mas-Collel address this point, perhaps in an exercise. Your intuition is right, the larger "t" is, the more deadweight loss there is, and this is reflected by transactions that do not occur. A large enough "t" can prevent all transactions from occurring, just as a large enough tax can kill a market.


How's a levered hedge fund effectively selling a gigantic put option on its ability to finance its own positions? I grasp the basics of a put option. John C. Hull. Options, Futures, and Other Derivatives (2017 10 edn).  pp 8-9.

  A put option gives the holder the right to sell the underlying asset by a certain date for a certain price.

Can someone please ELI5 the  bolded quote below?

"The Basis Monster that Ate Wall Street" (PDF). DE Shaw & Co. March 2009. p 3 of 9.

  Of course, the value and even the sign of the cash-synthetic
  basis vary over time. If obliged to guess prior to the present
  financial crisis, most market participants probably would have
  ventured that a basis position that was long the cash
  instrument actually would have outperformed (that is, the
  basis would have become more positive) in a crisis, as
  worried investors would be expected to buy protection in the
  form of CDS, thereby pushing credit spreads on CDS wider
  than those on the underlying cash bonds. A research report
  issued by Lehman Brothers in August 2005, for example,
  noted that "hedging demand amid increased market
  volatility kept CDS spreads wider relative to cash."' But
  events have unfolded very differently in this crisis While the
  long cash/short synthetic bases of a few issuers may have
  outperformed, that's not been the case for the majority of
  issuers during this now protracted financial crisis, and a
  decision to put on long cash/short derivative trades as a rough
  form of crisis insurance would not have worked out very well.

  What's critical here is that the two risk factors most
  responsible for driving cash-synthetic basis—namely, the
  availability of financing and the positioning (long or short
  cash relative to synthetic) of levered players—are quite

p 4 of 9.

  inconveniently also two of the least desirable risk factors for a
  levered investment vehicle like most hedge funds. Those
  factors' combined impact literally describes the terms of a
  classic common-investor liquidation crisis. By incurring heavy
  exposure to financing risk and the portfolios of other levered
  investors, a levered hedge fund is effectively selling a gigantic
  put option on its ability to finance its own positions.
  Moreover, this put option has characteristics that greatly
  increase the probability that the option will move in the
  money at the worst possible moment. If a levered investor
  suddenly finds itself facing heavy losses, it's not a stretch to
  suppose that, at the same time and for largely the same
  reasons, that investor's equity capital base is under pressure
  from redemptions, its financing position is weakening
  because of a credit crunch, and other similarly positioned
  investors are liquidating. Worse still, all of these phenomena
  tend to self-reinforce in pernicious ways. In such
  circumstances, it's imprudent to count on financing and
  trading counterparties to provide help because, as already
  noted, they're likely to be deleveraging at the same time.

This was a really good question, and a fascinating topic (one that was admittedly hard to wrap my head around). I found a great video on this topic here.
When people say you're selling a (cheap) put option, they generally imply you're taking a needlessly big risk for only marginal upside. For example: not having adequate cash in your portfolio is essentially selling a cheap put on your liquidity. You get the marginal gain of avoiding cash drag...but you get absolutely steam-rolled if you're hit by a margin call. Best case you enjoy extra 1% / year, worst case you get annihilated. Seems asymmetric, no? I think that's what they're implying.
So, in an ideal world, you take JUST the position of cash-synthetic basis mispricing. BUT, DE's point is you're taking that risk PLUS the risk of whether or not other leveraged hedge funds can finance their position. Ominously enough, you're likely part of that "leveraged hedge fund" group yourself. If a competitor loses their financing, they will have to liquidate their trade. If they liquidate, it makes the mispricing WORSE. As they liquidate (and your trade moves against you), you likely ALSO have to liquidate because your financing is also drying up. All of these things would happen at once, and would self-reinforce.
Put succinctly, you are taking two co-amplifying risks (financing options + basis mispricing) - but only really getting paid for one of them (basis mispricing).
Does that hopefully help?
Cash-Synthetic Mispricing
This is essentially when you can buy a bond yielding 3% / year, and then turn around & buy insurance on it for 2% / year. It is riskless arbitrage...and theoretically Capitalism should compete it away. The difference between my numbers above (the 2% and 3%) is the "Cash-Synthetic Basis" referenced in the DE Shaw article.
"Cash" is a misnomer that refers to the actual underlying bond. "Synthetic" means a CDS, or some sort of synthetic instrument.


Is manufacturing automation really a bad thing for the economy? Media loves to create a technophobia frenzy for automation and robots. Would REALLY automation in manufacturing cause the economy to collapse?

Taking an extreme case that is impossible to happen even in the far future due to technical challenges, but consider that EVERY job is replaced by robots. Manufacturing of a product from start to finish would be done by robots and no work from humans necessary. This product would essentially be for FREE. Shouldn't this the ultimate goal of an economy?

Ignoring this dystopia society, even if automation replaces some of the more redundant jobs, like taxi drivers, truck drivers etc. Wouldn't that allow for reassignment of human resources to more important tasks and help the economy grow?

I think the situation is similar to the introduction of steam machines and the fear people had about them replacing men. While in reality they didn't replace them, they re-assigned them to positions that required more skill and knowledge (Such as machine mechanic etc)

I don't see any way that automation in manufacturing is a bad thing. Our society is more data and knowledge focused and I think the ones that are afraid are the ones incapable of expanding their knowledge, learning a new skill or adopting to the changes. But should we stunt the growth of our society due to few lazy, unskilled people and literally wait until they die to introduce progress?

I believe that any human in order to survive will adopt and the people mentioned above are no exception.

As an answer let me offer a paradox that goes in your direction and is related to automation and the future of jobs:

  Despite a century of creating machines to do our work for us, the
  proportion of adults in the US with a job has consistently gone up for
  the past 125 years. Why hasn't human labor become redundant and our
  skills obsolete? In this talk about the future of work, economist
  David Autor addresses the question of why there are still so many jobs
  and comes up with a surprising, hopeful answer.

Here is David Autor's TEDx Why are there still so many jobs? and I will have added [despite automation]

Autor's answer is that technology magnifies the importance of our expertise and creativity and since we never get enough the wealth and the time saved by automation boost our endless inventiveness. So, automation will NOT replace EVERY job by robots. There's always new work to do.

The challenge that this automation phenomenon creates, what economists call job polarization, is that it knocks out rungs in the economic ladder, and shrinks the size of the middle class. The share of employment in occupations in the middle of the skill distribution has declined rapidly in the US and Europe. At the same time the share of employment at the upper and lower ends of the occupational skill distribution has increased substantially. A compelling explanation of this job polarization is that middle-skilled manufacturing and clerical occupations are characterized by a high intensity of procedural, rule-based activities which they call "routine tasks", which can relatively easily be coded into computer programs (see Autor, Levy, and Murnane, QJE, 2003).

Update

Daron Acemoglu and Pascual Restrepo have new working papers tackling this important question.

Robots and Jobs: Evidence from US Labor Markets
Automation and New Tasks: The Implications of the Task Content of
Technology for Labor Demand
Demographics and Automation

Abstract of Automation and New Tasks: The Implications of the Task Content of
   Technology for Labor Demand  [emphasis mine]

  We present a framework for understanding the effects of automation and
  other types of technological changes on labor demand, and use it for
  interpreting changes in US employment over the recent past. Automation
  enables capital to replace labor in tasks it was previously engaged
  in. Because of the displacement effect it generates, automation is
  qualitatively different from factor-augmenting  technological changes;
  it always reduces the labor share in value added (of an industry or
  economy) and may also reduce employment and wages even as it raises
  productivity. The effects of automation are counterbalanced by the
  creation of new tasks in which labor has a comparative advantage,
  which generates a reinstatement effect raising the labor share and
  labor demand by expanding the set of tasks allocated to labor. We show
  how the role of changes in the task content of production—due to
  automation and new tasks—can be inferred from industry- level data.
  Our empirical exercise suggests that the slower growth of employment
  over the last three decades is accounted for by an acceleration in the
  displacement effect, especially in manufacturing, a weaker
  reinstatement effect, and slower growth of productivity than in
  previous decades.


Pareto Efficient level of Public Good As part of self study towards an entrance exam, I am solving the following question.

There are two consumers in the economy and two goods, one private and one public. The utilities of the consumers is given by:

$$u_1(x_1,y) = x_1+6\sqrt y$$

$$u_2(x_2,y = x_2 + 10\sqrt y$$

where $x_i$ is the quantity of the private good and $y$ is the quantity of the public good consumed. Initial endowments of the private goods:

$$\omega_1 = 40, \omega_2 = 60$$.

A unit of private good can be converted one-for-one to a public good.

My attempt:

The Pareto Efficient level of public good is determined by the equation:

$$|MRS_1| + |MRS_2| = MC(G) \quad (1)$$

where $MRS_1 = \frac{MU_G}{MU_{x_1}}$, $MRS_2 = \frac{MU_G}{MU_{x_2}}$ and $MC(G)$ is the marginal cost of providing the public good.

Solving $(1)$ with the given utility functions I get:

$$\frac{3}{\sqrt y} + \frac{5}{\sqrt y} = 1$$
$$\implies y = 64$$

Therefore, the Pareto efficient level of public good is $y=64$.

The question asks to select the Pareto Inefficient bundle $(x_1,x_2,y)$ amongst the following:

A. $(50,0,50)$

B. $(90,0,10)$

C. $(0,80,20)$

D. $(16,20,64)$

I think all of A, B and C are Pareto Inefficient.

The given answer is C.

Thanks for reading my question.

The social welfare maximizing outcome you computed (by equating the sum of marginal benefits to marginal cost) is just one of the Pareto efficient outcomes. Although maximization of joint utilities is a sufficient condition for Pareto efficiency, it is not a necessary condition. Pareto efficiency is defined by the lack of Pareto improvement -- a reallocation of resources to make at least someone better off without making any other worse off.

Option C is not Pareto efficient because a Pareto improvement exists. At $(0,80,20)$,
\begin{equation}
u_1(0,20)=0+6\sqrt{20}\approx 26.83 \qquad
u_2(80,20)=80+10\sqrt{20}\approx124.72.
\end{equation}
Observe that at this bundle, consumer 2's MU for the good $y$ is $5/\sqrt{20}\approx1.11$ and his MU for $x$ is $1$. Therefore, increasing one unit of good $y$ at the expense of one less unit of $x$ is utility enhancing for consumer 2. At the same time, one extra $y$ benefits consumer 1 as well. So we can easily verify that $(0,79,21)$ is a Pareto improvement over $(0,80,20)$:
\begin{equation}
u_1(0,21)=0+6\sqrt{21}\approx27.495 \qquad
u_2(79,21)=79+10\sqrt{21}\approx124.83
\end{equation}
where both consumers experience higher utilities.

In a similar way, you should be able to verify that no Pareto improvements exist for options A, B, and D.


Has the ban of single-use plastics sparked innovation in biodedgradable recyclable plastics? One of the rationales of the single-use plastics ban adopted by the EP in 2019 is that it will spark innovation in cheap biodegradable recyclable plastics. Has any progress been registered in this regard?

Not sure if this question is suitable for this site but here's some (unsubstantiated by data) information and some other interesting points relating to economics behind it.
Rationale of the ban is not unfounded. It is based on a rather simple concept famously known as the Porter's Hypothesis. However, there is more economics at play (explained below). But that later
Coming to innovation: there is some evidence of innovation in biodegradable plastics. For example, in flights the plastic spoons/forks and knife given with packed food are now made of biodegradable plastic. Now the biodegradable plastic material is not even remotely as strong or malleable as regular plastic. But with right mechanics and design, the industry has finally been able to come up with usable (not necessarily affordable) cutlery. This we can definitely consider innovation.
But that is not all that is happening. One can certainly argue that if it were possible to make biodegradable plastic cutlery why did it not happen earlier? The simple answer is it was expensive. The biodegradable plastic cutlery is heavier compared to plastic counterpart and the raw material (which comes by weight) is also more expensive. It was because of regulation that industry was forced to take away from market the cheaper (and at that time - far better) alternative.
This is step one. Step two of the intended consequence is the new product becoming economical. So interestingly (unfortunately, I am unable to find the article now), the price of biodegradable plastic (usually corn byproduct or similar something) is increasingly becoming more affordable (economies of scale). The design is being copied and adopted by many take-away restaurants. So you see, perhaps in foreseeable future, even if the regulation is removed, industry may continue to keep using biodegradable products.
So if all goes well, it becomes a win-win in few years time.
As an economics student, what's of interest is that a pareto improvement outcome (an outcome which is favourable for some and not unfavourable for any) was just lying there. However, market outcomes are seemingly not that far-sighted and therefore often requires a nudge to set it moving in the right direction.
You can relate this to many things: fuel efficient car engines, battery driven cars, lending to small entrepreneurs and what not!


external benefit confusion I'm a little confused by the following question and answer provided by MRU:

Fruit farmers pay beekeepers for their honeybees’ pollination
services. Honeybees provide an external benefit to fruit farmers.
However, fruits provide an external benefit to the beekeepers because
their honeybees need fruits. Which external benefit is larger:
honeybees’ external benefit to fruit farmers and fruits’ external
benefit to beekeepers?

Their answer:

Honeybees’ external benefit to fruit farmers is larger

This seems like the least fitting answer to me.  The fruit farmers pay the beekeepers for their services, so the benefits they get from this relationship are mostly accounted for by the cost.  However, beekeepers don't have to pay the farmers for the benefit their bees get from pollinating their plants, so this benefit is an external benefit that farmers give to beekeepers.  Am I misunderstanding something here?

Not sure I understand your confusion.
Fruits provide external benefits worth $X$ to honeybees, honeybees provide external benefits worth $Y$ to fruits.
Knowing all this, farmers and beekeepers agreed that farmers should pay beekeepers amount $Z$, which probably comes close to making things even, meaning $X + Z = Y - Z$. Since $Z > 0$, $X < Y$.


Why don't economists recommend voluntary childlessness to fight poverty? Please see the titled question. Poverty obviously demands pressing  solutions, let alone a stopgap. Dasgupta beneath refers to "the best Desta’s world can do": isn't Voluntary childlessness and Antinatalism more effective and instant? Kids who play and scavenge in garbage, and who live in sewers may argue that it was better never to have been born. Harms of their existences are obvious:

For those who still crave children, why isn't adoption recommended?  I refer only to educating the indigent;  anything involuntary like eugenics  is unethical.

Dasgupta, Partha. Economics: A Very Short Introduction (2007).
p. 159 Bottom

In a moving discourse on the character of poverty at the 2001
Plenary Meeting of the Pontifical Academy of Social Sciences,
Vatican, Justice Nicholas McNally of Zimbabwe urged us all to see
poverty as a sense of fatalism to ever-increasing economic
hardships in a changing, and elsewhere an often progressive, world.
At that same meeting, the political scientist Wilfrido Villacorta
suggested that the term ‘poor’ when applied to countries is perhaps
no longer useful; that countries ought perhaps now to be classified
in accordance with some such term as ‘progressive’, so that we may
ask if they have the institutions, policies, and civic attitudes in place
to enable people to improve their lot. Perhaps the best Becky’s world
can do for Desta’s is to offer financial and technical assistance so as
to promote and support local enterprises – including those

p. 160

involving education and primary health care – that people there are
all too keen to create even as they see from a distance how people
elsewhere have been able to improve their conditions of living. And
perhaps the best Desta’s world can do for Becky’s is to alert it to the
enormous stresses economic growth there has put on Nature. There
is, alas, no magic potion for bringing about economic progress in
either world. [I bolded]

p. 102

Gender inequalities
The considerations I have just outlined can’t on their own explain
the persistence and magnitude of household inequalities in the poor
world. In a notable article, the demographer Pravin Visaria
observed that the female–male ratio in India had shown a decline
since the Indian Census of 1901; worse, it has been considerably less
than 1. According to the most recent census, there are 93 women to
every 100 men in India. In the rich world today, the ratio is 106 to
100. In answering a question the epidemiologist Lincoln Chen
posed in response to Visaria’s finding, namely, ‘Where have the
women gone?’, he and his collaborators collected gender-based
mortality and anthropometric statistics from villages in the Indian
sub-continent and discovered male bias in the allocation of food
and health care in poor households. The suspicion is that parents
not only practise female infanticide, but also withhold postnatal
health care so as to reduce the number of girls in the household. [I bolded]

Economics: The User's Guide. p. 334.

 Inadequate childhood nutrition, lack of learning stimulus and sub-par schools (frequently found in poor neighbourhoods) restrict the development of poor children, diminishing their future prospects. Parents may have some control over how much nutrition and learning stimulus their children get – and some poor parents, to their credit, make great efforts and provide more of those things than do other parents in similar situations – but there is a limit to what they can do. They are by definition under great financial stress. Many of them are totally exhausted from juggling two or three insecure jobs. And most of them had a poor childhood and poor education themselves.

Despite the initial shock value provided for the question, and the high possibility for this question to become heated, political, or otherwise delve into an off-topic conversation, I will do my best to provide an answer to this question.

  Voluntary childlessness would be a functionally ineffective suggestion. This is not only too vague a suggestion to be widely useful or create policy for, but there are better focuses for economists to study in order to fight poverty.

If adults are practicing female infanticide for cultural or economic reasons, would these adults seriously consider simply not having children if you ask them? If adults are withholding post-natal care in particular circumstances, then how is this an economic failure rather than a moral one? If we are focusing on the family unit, and argue that every family has its own smaller market economy in who provides what sort of labor for the family, then shouldn't we argue that each family economy should be informed on how to make better choices, and be restricted from making unethical choices such as murder?

In some cases, maybe a family might consider not having kids if they can't support them. The consideration for whether someone will have a reasonable quality of life of course is subjective. In some parts of America there is extreme poverty, same as there is in India or China or many other countries. Yet happiness or "utility" has always been a subjective experience, and families continue to have children in these conditions.

Consider this statement from Indian economist and Nobel Prize winner Amartya Sen:

  "There is considerable empirical evidence that even as people in many parts of the world have become richer, with much more income to spend in real terms than ever before, they have not felt particularly happier than before.1 "

As with all things this may not be universally true. Some studies find suicide rates are not sensitive to income or unemployment. 2 But what is a bad living standard for some is not an insurmountable living standard for others. Is it wrong for people to bring children into the world where they must overcome suffering? Answering this question requires imposing a hard standard for what standard of living is a basic right, which frankly, is not the intellectual right of economists over everyday people.

Responsible economists, if looking at this issue, would rather prevent the miniature market failures within the family unit. Sometimes, trying to make policy that greatly restricts choice at the small scale would be impractical, or too prohibitive to be ethical, as economists generally like to allow for individual freedoms. So economists tend to look at broader policy through taxes or social welfare programs to combat poverty. One thing that is clear is that to prevent the most egregious consequences of poverty, there must be a way to hold those accountable who commit atrocities such as female infanticide or other such actions.

  "It was mentioned in the last chapter that no major famine has ever occurred in a functioning democracy with regular elections, opposition parties, basic freedom of speech and a relatively free media (even when the country is so poor and in a seriously adverse food situation)....Despite China's greater economic success than India's in many economic fields, China - unlike independent India - did have a huge famine, indeed the largest famine in recorded history, in 1958-61, with a mortality count estimated at close to 30 million. Though the famine raged for three years, the government was not pressed to change its disastrous policies3"

If transparency and public accountability are required to prevent and act on national tragedies that greatly reduce welfare, then on the smaller scale, the culture within a community is what will determine whether poverty or crises of resources will be answered with some sort of aid or assistance, or whether they will be answered with more drastic measures.

One cannot ignore in this conversation that many modern economies actively encourage population growth. As mentioned above in the comments, some places like Communist China had a one-child policy to restrict population growth. That policy has been repealed in the face of the changing demographics that China is undergoing, where there will be a much larger proportion of older people who live longer. The one child policy was a contrived way of dealing with issues like food shortages. Because the government tried to completely control markets, they created weird market failures and dealt with them in ways that were clearly detrimental.

Does this mean policies such as giving tax breaks to those who marry or giving welfare based on household size are bad policies? Is there moral hazard in subsidizing child creation in some sense? First off, why do these policies exist? An economy can grow both with the creation of technology, and the creation of capital and labor which pair together at some "efficient" ratio, depending on the market. To perhaps oversimplify, growing labor is one of the ways of growing an economy and trying to keep it productive and competitive with other countries.

Thus, economists should study how welfare programs for families affect the incentives families have for working or having children, etc. Which they already do. A cursory search of the literature:

Maru, Rushikesh M. "Incentives and disincentives in the Indian family welfare program." Studies in family planning 17, no. 3 (1986): 136-145.
Knox, Virginia W., Cynthia Miller, and Lisa A. Gennetian. Reforming welfare and rewarding work: A summary of the final report on the Minnesota Family Investment Program. Vol. 8. New York: Manpower Demonstration Research Corporation, 2000.
Keane, Michael, and Robert Moffitt. "A structural model of multiple welfare program participation and labor supply." International economic review (1998): 553-589.
Dahl, Gordon B., Andreas Ravndal Kostøl, and Magne Mogstad. "Family welfare cultures." The Quarterly Journal of Economics 129, no. 4 (2014): 1711-1752.
Schoeni, Robert F., and Rebecca M. Blank. What has welfare reform accomplished? Impacts on welfare participation, employment, income, poverty, and family structure. No. w7627. National bureau of economic research, 2000.
Lundberg, Shelly, and Robert D. Plotnick. "Adolescent premarital childbearing: Do economic incentives matter?." Journal of Labor Economics 13, no. 2 (1995): 177-200.

At the end of the day, economists are not concerned necessarily with changing the minds of individual family members and encouraging them to not have children. A family may not even find this "optimal", as children are a source of not just future support into old age, but of companionship in a harsh world (and other non-pecuniary incentives). Energy is better directed at guiding the hand of government towards policy that can effectively alleviate poverty and increase the welfare of society as a whole.

Additional citations:

1 Sen, Amartya Kumar. The idea of justice. Harvard University Press, 2009. 272.
2 Andres, Antonio Rodriguez. "Income inequality, unemployment, and suicide: a panel data analysis of 15 European countries." Applied Economics 37, no. 4 (2005): 439-451.
3 Sen, Amartya Kumar. The idea of justice. Harvard University Press, 2009. 342.


How can we measure the size of the new uber-driver-type economy? Uber has probably hundreds of thousands of drivers just in the US. There are many other gig economy firms growing quickly, not only lyft, but also Amazon Prime, bite squad, etc. Is there some place in the data that we can observe this happening? Is there a number that has been growing quickly for part time, self employed maybe? Is there a number in the Social Security statistics? More generally, how do we measure the actual size of this relative to the US labor force? Maybe we should look at the fraction of self-employed people in the US?

Those are important and difficult questions to answer. Regarding Uber, Jonathan Hall (Uber) and Alan Krueger (Princeton) wrote a joint paper on An Analysis of the Labor Market for Uber's Driver-Partners in the United States. The paper provides the first comprehensive analysis of Uber's driver-partners, based on both survey data and anonymized, aggregated administrative data. The following figure documents the exponential growth in the number of active Uber driver-partners in the United States from mid-2012, when uberX was launched, to late 2014.

Source: Hall and Krueger (2015)

More generally, they point out that the Bureau of Labor Statistics (BLS) publishes a supplemental module to collect information on various forms of contingent and alternative work arrangements in the Current Population Survey (CPS) in 1995, 2001, and 2005 that provides the most informative data available, although it is now somewhat out of date. The BLS contingent worker supplement also measured the share of workers in alternative work arrangements, including independent contractors. Workers in the sharing economy can work part-time or full-time, or participate on a temporary or permanent basis, but they are almost universally working as independent contractors while they are participating in the sharing economy. Thus, evidence on independent contractors can provide relevant background for understanding the nature of the labor market in a sector that overlaps with the sharing economy.


Randomisation and balance in experiments Suppose we are interested in the effect of some 'treatment' on some outcome of interest. A common practice is to select a group of people and then randomly choose some fraction (often half) to receive the treatment. The remaining people are untreated (i.e. the 'control'). As shown in (e.g.) Angrist and Pischke, the difference in mean outcomes between the groups is then an unbiased estimate of the average causal effect of the treatment.

While such a procedure does give us an unbiased estimate, it does not ensure that the treatment and control group are 'balanced' on observable criteria. For example, although on average there will be the same fraction of men in the treated and untreated groups, in our actual sample there are likely to be a higher fraction of men in one group. In such a situation, it seems natural to simply take some men from the 'overly male' group and place them in the 'overly female group' until the gender ratio is the same in both groups. (If we wanted, we could select the men we choose randomly.)

Some questions:

If we do this, will the difference in mean outcomes between treated and untreated groups remain an unbiased estimate of the causal effect?
If so, why is this not done in all RCTs?
If not, how do we trade-off the benefits of achieving 'balance' against the possible bias that we are introducing?

Optional extra: I am aware that this procedure seems rather similar to 'stratification'. However, my understanding is that, after stratifying, people do not compare mean outcomes for the treated and untreated groups (rather, they compare mean outcomes for every subsample on which they stratified, or equivalently run a regression with stratification dummies). If my proposal is indeed equivalent to stratification, my question is then equivalent to the question why we need these dummies and what are the costs and benefits of stratification.

Ok, I am far from an econometrician, but my train of thought would be as follows:

By using random assignment we have two groups that are on average equal to one another on all aspects. As you rightly point out due to sampling variation there will be differences.

My worry would be that if I start "correcting" those after randomization (as per your example with gender distribution) I introduce other differences between the groups in say age or even an unobserved but important characteristic.

Stratification is different as it is done upfront. You have a characteristic that you know is different for different groups so you take the random samples within those groups. As a rather naive example: we know that the effect of taking anticonception pills is rather different for men and women, so if you wanted to test the effect of the pill on fertility you could stratify by sex and then do a random assignment within the sexes.


Uncovered interest parity and asymmetric capital controls To derive the uncovered interest parity (UIP) condition we assume, among other things, that there is free movement of capital across countries.

But this cannot be directly applied to India because of capital controls. While foreigners are relatively free to hold Indian assets, Indians are in general forbidden to hold foreign assets.

Is there a variant of the UIP that we can expect to hold (given the other assumptions) under such asymmetric restrictions on asset holding?

In principle it shouldn't really matter that a sub-population (in this case the locals) have capital restrictions, so long as the unrestricted population is sufficiently large.  The UIP model only needs that the capital can flow - it doesn't mind who is doing it.

In this case, so long as the foreign investors have not completely left, then in aggregate the restriction shouldn't make a difference.

Furthermore, if foreign investors are able to short sell to locals (which I think they can?), then you can even create extreme capital outflows.


Why is increased productivity infinitely good From investopedia:

  Supply rises with productivity, dropping real prices and increasing
  real wages; it lifts people out of poverty and allows them to focus on
  efforts beyond mere survival.

I thought I was naive so I asked google why productivity was always good in economics and this is "google's answer."  Does economics really assume that whatever work a human does, doing it less and something else more is always better for them?

Productivity gains either allow to produce more with constant inputs, or to produce the same amount as before with fewer inputs. It is to individuals and firms to decide what to do do with productivity gains. In a market economy, the price and wage
adjustments induced by productivity changes help individuals to decide whether to work less or more, to invest and hire more employees, etc.

Usually productivity gains do not fall from heaven, firms and individuals have to pay for it (R&D, organizational change, etc) so it is not necessarily good, it is however welfare
improving if the price paid to achieve productivity gains does not increase the benefits (private or public). How costs and benefits from productivity changes are shared
in order to promote both equity and further productivity gains is a challenging societal and political issue.

Contrary to the claim of your citation, productivity gains do not systematically increase wages, it depends on the technology and the structure of the commodity and labour market.


“Consumption lowers investment” mankiw explanation I am teaching myself macroeconomics and I am stuck on this reading Mankiw:

  Because the economy’s output is fixed by the factors of production and
  the level of government purchases is fixed by the government, the
  increase in consumption must be met by a decrease in investment.
  For investment to fall, the interest rate must rise. Hence, a
  reduction in taxes, like an increase in government purchases, crowds
  out investment and raises the interest rate

Before that, we have the fined the following identity:

Y - C - G = I

Output - Consumption - Gov. spending = Investment.

Looking at the identity, it’s easy to see why the bolded part is right, but I can’t intuitively understand why an increase in consumption would decrease investment.

This is because investment is equal to private and public savings (but assuming balanced budget public saving drops out so it would only be private savings I=S). This is because you can only invest what you save.

Moreover saving and consumption are mutually exclusive. From your income you can either consume or save there is no third option economically speaking (actually technically saving is postponed consumption but I don’t want to confuse you too much so I won’t go further into that).

Hence it’s quite intuitive that the more you consume, the less savings available and the higher the interest rate due to low savings and so on.

So to sum up consumption must decrease investment as the more proportion of your income you consume the less you can save. If you consume 70% of your income you can only save 30%, if you consume 90% you can only save 10% and so on. If you consume 100% of your income your saving and thus investment is 0.


Converting monthly data to quarterly I have monthly shock series, which I want to convert to quarterly form. I have seen several methods like taking average of 3 months or summing 3 months for making a quarter. I would like to know how I can know which method is useful for me. Taking average or summing? Or is it something about personal choice in research methodology?
More details:
I intend to get impulse responses of real GDP to news shocks (which are already available). My GDP series are in quarterly form and my shock series in monthly form. So I need to convert shock series to quarterly form and do local projections.

I've seen them summed somewhere but I cannot exactly remember where. Ultimately I don't think that it makes much difference. The quarterly sum is just the average multiplied by three. Since local projections are just a bunch of OLS - one for each horizon, this is how you can think about the issue:
If $y_{t+h} = \alpha^h + \beta_h news\_shock_t + \sum_{j=1}^{L}\delta_j^hx_{t-j} + \dots + \sum_{j=1}^{L}\gamma_j^hy_{t-j} + \epsilon^h$ is the OLS for the h-th horizon, adding the shocks up is going to yield a $\beta_h$ that is exactly three times smaller than the $\beta_h$ you will obtain by averaging. The statistical significance will not be affected.
Since the units of the news shock most likely don't have any particular meaning both regressions yield exactly the same information.
A different approach instead of aggregating the news shocks up is to use industrial production data, which is usually available on monthly basis to disaggregate the GDP series down to monthly levels using Chow-Lin interpolation. A recent paper using this method would be Anaya et. al..


Have there been attempts to measure the value of specific taught skills? I'm aware there is a body of research concerned with measuring the returns to schooling in general, and there are theoretical pronouncements about what the most valuable things to learn at school are.

Have there been any empirical attempts to estimate the value of being taught specific skills - for example, phonics or solving algebraic equations?

Have there been any empirical attempts to estimate the value of being taught specific skills - for example, phonics or solving algebraic equations?

If I may be brazen enough to challenge the basis of this question. We first need to have an economic criteria to evaluate a subject in a curriculum before we start analysing its relevance to the labour market .

I got all this information from the University of Mumbai- Economics of Education for M.A Education
. (free download and an easy read).

In terms of how an economist should view a curriculum, the criteria is twofold, as stated in the course kit:

  One needs to asses the value of the subject and its
  existence in the system.
   There are two criteria for a particular
  subject being studied or taught in a given course of study.

  1) Theoretical consideration:
  The subject should be a body of fundamental knowledge
  which is a prerequisite for the understanding of other subjects.

  2) Practical consideration:
   The subject should have a practical significance in the sense
  that its understanding would be useful in taking efficient decisions
  in some of the practical problems. (pg.108)

This being said, its inappropriate to measure productivity on the basis of knowledge of phonics and algebra as these are studies which are only prerequisites of more prerequisites for another subject with labour market implications.

Hope this helps