How do you reconcile the Law of Increasing Opportunity Costs and Economies of Scale? Marginal cost of production always increases, while marginal benefit of production decreases. As far as I understand, that is why the supply curve has positive slope and the demand curve negative slope.

I don't understand, though, how this can be compatible with the "economies of scale" everyone is always talking about. One theory says increased production should increase marginal opportunity costs, while another says it should decrease marginal opportunity cost. So, what is actually going on?

You are correct that an uniformly increasing cost of production cannot exist alongside economies of scale. A constant returns to scale production function is homogeneous of degree one:
$$ f(\lambda x, \lambda y) =  \lambda  \cdot f(x, y)$$
That is, when you double all the inputs you also double the output. An increasing returns to scale production function is one for $\lambda > 1$ (so that you actually increase the resources) in which $f(\lambda x, \lambda y) >  \lambda  \cdot f(x, y)$  (e.g. double the inputs and more than double the outputs for at least some combinations of inputs). However, it is problematic for a production function to have increasing returns to scale for all levels of inputs. Increasing returns to scale means fewer and fewer inputs are needed for each marginal unit of output. This generally means that marginal cost of production is also falling. This has all sorts of bizarre consequences, including the potential for indeterminacy (multiple equilibrium levels of output), downward sloping supply curves, and equilibrium non-existence. We also don't generally think it is true in reality. It is widely observed that beyond a certain scale most industries do not exhibit further returns to scale. For some industries, like dry cleaning, this scale is quickly reached, for others, like automobile manufacturing or social networks it may be very large indeed. But we generally believe that eventually the marginal cost of production will rise with scale. Even if we bought exactly the same car in same color, we'd still eventually want so many that the cost of labor, rubber, and metal would rise from that demand, driving up the marginal cost. We also face dis-economies of scale like managerial incentive problems and other  difficulties of managing and controlling an increasingly large institution.

It is worth noting that you can have increasing returns to scale but decreasing marginal product of inputs. For example, the production function:
$$y(\ell, k) = \ell ^ {.75} \cdot k ^ {0.6}$$
has increasing returns to scale:
$$y(\lambda \ell, \lambda k) = \lambda^{1.35} \ell ^ {.75} \cdot k ^ {0.6} > \lambda \cdot  \ell ^ {.75} \cdot k ^ {0.6} $$
But holding fixed the other input, we can see that the marginal product of both $\ell$ and $k$ are decreasing in that input. E.g.:
$$ \frac{\partial y}{\partial \ell} = 0.75 \ell ^ {-0.25} \cdot k ^ {0.6}$$
$$ = 0.75 \frac{k ^ {0.6}} {\ell ^ {0.25}} $$
Similarly:
$$ \frac{\partial y}{\partial k} = 0.6 \ell ^ {0.75} \cdot k ^ {-0.4}$$
$$ = 0.6 \frac{\ell ^ {0.75}} {k ^ {0.4}} $$
We could also continue this and show that the second derivatives here were both negative, which means decreasing marginal product from each input
$$ \frac{\partial^2 y}{\partial \ell^2}  = -0.75\cdot 0.25 \frac{k ^ {0.6}}{ \ell ^ {1.25}}$$
$$ \frac{\partial^2 y}{\partial k^2}  = -0.6\cdot 0.4 \frac{\ell ^ {0.75}}{ \ell ^ {1.4}}$$

Note the cross-partial  is positive, which is how this economy still has increasing returns to scale:
$$ \frac{\partial y}{\partial \ell} \frac{\partial y}{\partial k} = 0.75 \cdot 0.6 \frac{1} { \ell ^ {0.25} \cdot k ^ {0.4}} > 0 $$
which is positive.

Both arguments show that the marginal product of the input decreases as the quantity of that input rises. This holds even though the production function shows increasing returns (and is actually homogeneous of degree 1.35).


What Creates the Price in the First Place I just wanted to know if price changes how much quantity is supplied or demanded then what creates the price in the first place?

If you say that price affects supply and demand and supply and demand affect price then this just sounds like circular logic to me.

Thanks

This is indeed a bit confusing. Supply and demand functions depend on potential prices. That is, the agents think "if the price were a given level, what would I want to supply or demand?". So supply and demand depend on a whole range of (hypothetical) prices. However, the equilibrium price (which is a certain price and different from the range of potential prices) is that price where both supply and demand meet. In your example, the equilibrium is where the circular logic stops and finds a resting point, which is also why we refer to it as an equilibrium. This is a concept, which we borrowed from physics and is often used to mean a position where things stop changing/moving.

You are right to ask, however, how this whole process is initialized.

The rigorous way to think about this for economists, is to use what is called a "Walrasian Auctioneer".

You can imagine the process as such. An auctioneer calls out prices. Suppliers report how much they wish to supply, whereas consumers report how much they wish to demand. If these do not meet, the auctioneer calls out other prices. This goes on until demand meets supply and that's when the auctioneer stops.

Of course in reality, there is no walrasian auctioneer. Nevertheless, it is not hard to imagine that a new firm sets some price when it starts and then adjusts it depending on demand. Furthermore, depending on that new suppliers might enter, which changes supply and causes the price to adjust again. This goes on until a stable point is found, which we call the equilibrium.


What is a dollar, currently? What is the definition of a dollar now without gold backing?  It seems that a dollar is now just an entry in a book somewhere in some bank.  Or it is the federal reserve note?  Or is it both?  I understand the concept of the monetary base.  But what I don't understand is how this works.  If a dollar is in part just an entry in a book, what stops some bank from simply claiming they have an infinite amount of dollars?  Or is there some central registry that claims to keep track of how many dollars each bank has? (This would seem absurd to me.  How then would foreign banks holding US dollars keep track of how many dollars they had?)  If there is no central registry, then how do you prevent people claiming to have dollars on their books?

I think explaining what a dollar is would go toward answering these questions.

A dollar is money which can be used in the United States to purchase goods and services and to repay debts. It can sometimes be used for these purposes in some other parts of the world.

If a bank says it has an unlimited amount of dollars, then it will presumably be willing to lend them to customers, who will then want to spend them.

The bank will then either have to give the customer dollar bills (Federal Reserve Notes which presumably it does not have in unlimited amounts) or be willing to transfer dollars to another bank on the instruction of its customer.

The other bank may then expect this to be settled.  Unless there are also flows into the first bank to offset the amount owed, it can only settle with dollar bills (but faces the same issue as before) or by instructing a third bank where it has an account to transfer dollars to the second bank.  This can continue up the chain until an instruction to transfer funds reaches the U.S. Federal Reserve Banks, where the top commercial banks hold their reserve deposits.

Other banks will not be impressed with the first bank simply saying it has unlimited dollars if it does not have accounts with other banks with dollars to support the transfers.  Writing numbers in your own books does not change the numbers in other banks' books.  The constraints that this causes is one of the constraints on lending and so on the creation of money.


Overview book about economic theories I'm looking for a good book that gives an (introductory) overview about the existing economic theories and the different schools of thought (optimally with focus to those that affect governments and institutions). Presentations that use  mathematical formalisms and that give a little bit of historical background to the respective theory are very welcome. I don't have any economic education, so I am hoping that there exist some "standard works" that compare the different theories and schools of thought.

Snowdon and Vane "Modern Macroeconomics: Its Origins, Development And Current State" is probably the best book I have read which gives a clear exposition of all the major macroeoconomic schools from the classicals to the New Keynesians. It highlights what the different schools have contributed to modern macroeoconomics and compares them to the other schools. They even include interviews with economists such as Robert Lucas Jr. and Milton Friedman to mention a few. I guess this is exactly the book you are looking for and to be honest I think every single person studying economics should read this book. It is not an introductionary economics book but I think most people should be able to read and understand it.


Calculating marginal tax rates when near a cliff When using tax and transfer microsimulation models, a common approach for calculating marginal tax rates is to recalculate the tax liability when adding $1 to earnings. This will take into account various tax laws that interact in complex ways.

However, this will generally miss the effects of cliffs, such as losing Medicaid, ACA subsidies, or SSDI, unless a household is $1 below the threshold.

Is there a best practice to deal with this? A couple ideas come to mind:

Recalculate the tax liability for multiple changes to earnings, such as $1, $100, $1,000, etc., and weigh the results by the distance (e.g. 1/x).
Make copies of the underlying data, varying the initial earnings within some range, e.g. +/- $1,000, possibly oversampling near the true earnings (e.g. triangular distribution).

The marginal tax rate is supposed to reflect incentives for the individual. In order to derive a meaningful metric, the calculation should hence try to reflect the actual decision an individual is facing. An increase in \$1 pay is probably not something people are considering. If, however, someone earning \$10 per hour considers to increase his/her labor supply from 35 to 37 hours per week, you will end up with a pay increase of sth like \$1,000 per year. So I'm rather sympathetic to the \$1,000 step than to the $1 step.

The OECD also applies a change in hours worked to obtain the change in gross income used for calculating marginal tax rates.


Do the three ways of measuring producer’s surplus give the same result? In the Firm supply chapter of the microeconomics Varian's book, they show "three equivalent ways to measure producer’s surplus" using marginal cost, average cost and the average variable cost curves.

But my teacher says, "those three ways give different results. You have to keep the same method during a given analysis".

So are they or not giving the same result?

Intuitively I think they do give the same result and do not understand why my teacher says they do not.

Ask your teacher what he meant, because there is either a misunderstanding or he is mistaken.

Producer's surplus will come down to $y \cdot p - VC(y)$.

In the first graph, by definition of $AVC$ we have
$$
y \cdot (p - AVC(y)) = y \cdot p - VC(y).
$$
In the second graph, using $\int MC = VC$ and $VC(0) = 0$, we have
$$
\int_0^y p - MC(x) \text{d} x =
\left[x \cdot p - VC(x)\right]_0^y = y \cdot p - VC(y).
$$
The area in the third graph is
$$
\begin{align*}
\int_0^z p - AVC(z) \text{d} x +
\int_z^y p - MC(x) \text{d} x.
\end{align*}
$$
Let us calculate it by parts:
$$
\begin{align*}
\int_0^z p - AVC(z) \text{d} x & = z \cdot p - z \cdot AVC(z) = z \cdot p -  VC(z) \\
 \\
\int_z^y p - MC(x) \text{d} x & = (y - z) \cdot p - VC(y) + VC(z).
\end{align*}
$$
Summing up the two, we get $y \cdot p - VC(y)$.


Strict preference and utility function If strict preferences over three outcomes x, y and z, do not satisfy transitivity, so that $x \succ y \succ z \succ x$, then these preferences cannot be represented by a utility function.

Is this statement true or false? Can anyone explain it to me?

In fact, we don not even call them preferences. In order for a binary relationship to be a preference relationship, it must be both complete and transitive. The main goal of modelling preferences is to understand choice. And we cannot understand choice unless preferences are a quasi-order, i.e., one can rank alternatives (with ties allowed). In the case you mention, $x \succ y \succ z \succ x$, we would not know how to rank them. Further, it is clear that no function $u(·)$ can reproduce this ranking, as transitivity of real numbers makes it impossible to have $u(x)>u(y)>u(z)>u(x)$.

Note that this is different from $x \sim y \sim z.$ In this case you could say "no ranking exists" (although, perhaps it would be more adequate to say that "any ranking is consistent with the preferences"). In these circumstances, the utility function does exist, as it only must happen that $u(x)=u(y)=u(z)$.


why federal fund rate vs treasury bond yield generally move in the same direction? My own thought is, if the fed lowred federal fund rate, peoole should look for investment with greater return, like treasury bond. More demand=decline in yields but why do they generally move in the same derection?. Same goes for Mortgage rate during 2001-2005, why would mortgage rate go down if all the fed did was just lowering federal fund rate which has nothhing to do with mortgage?

Federal funds rate is a rate at which banks can borrow extra money at an overnight market. This can be viewed as 'banks' cost' since when people want to lend from certain bank, the bank will often get the money not from some new deposits it itself attracts but from the overnight market.
Consequently if the Fed funds rate drops they can afford to lend money more cheaply. The reason why they also do so instead of pocketing all the difference as a higher profit is the competition amongst the bank.  If you want to completely see the mechanism laid bare you can have look at chapter 3 of Freixas and Rochet, Microeconomics of banking. Hence this is the reason why mortgage rates will fall as well. Banks simply can create those mortgages more cheaply now.
The bond yield is also affected by the above. The current bond yield ($Y$) is given as:
$$Y = \frac{C}{A}$$
where $C$ is the annual coupon payment and $A$ is the asset price. The coupons are already fixed so bond which pays ${\\\$}100$ coupon and trades for ${\\\$}1100$ will have yield of $\approx 9\%$. Now whether that $9\%$ is a lot or not depends on prevailing interest rate. If the interest rate  is $10\%$ then yield of $9\%$ is small and if interest rate is $5\%$ yield of $9\%$ is high.
If the interest rate falls relatively to the yield the bond will get more desirable (like the situation when interest rate would be $5\%$ and yield $9\%$. In such case people will simply demand more bonds and then you will get the standard supply-demand story. People will bid the bond prices until $A$ increases sufficiently enough so people are indifferent between buying bond and putting money in some deposit account bearing that $5\%$ interest (or some other instruments). As you can clearly see from the formula above, higher bond price will imply lower yield. Hence when interest rate falls yield prices fall as well.


Existence of pure strategy Nash equilibrium I understand the reason why mixed strategy Nash equilibrium exists. But what are the conditions for the existence of pure strategy Nash equilibrium?

The most simple example is the example of unlimited periods and Bertrand pricing, in any given period the "pure strategy" (with 2 firms) is to produce 1/2 of monopolist quantity and sell at monopolist price and recieve profits = π(1-d)^t
Where d is discount value
t is period
Any deviation will result in 0 profits every period following the deviation, thus in an infinite period model is not worth it.


Simple Determinant of Supply Question Let's say we have ethanol and chips, both of which are made off of corn. If the production of ethanol is subsidized by the government, what happens to the supply of chips? The way I see this, more ethanol will be produced and more corn will be consumed, and so less corn will be reserved for chips, and so the supply of chips decreases. Am I right in this train of thought?

The supply of chips will probably decrease, although the situation is a bit more complicated than you describe.

The subsidy will tend to increase demand for corn by ethanol producers, both existing producers expanding production and new producers entering the industry. Increased demand for corn for ethanol production may have two effects:

More corn will be sold to ethanol producers.  If total corn production were unchanged, less corn would be sold to chip producers and the supply of chips would decrease.
However, total corn production will probably increase because the increased demand for corn for ethanol production will increase the profitability of growing corn relative to that of other crops or other land uses.  So the likely effect will be that corn is grown on land previously used for other crops, or possibly more land is brought into cultivation. In the medium term (since changes in land use take time) this could partly offset any decrease in the supply of chips.


Could the Feds objectives be adjusted to decrease or at least not increase wealth inequality? The US congress "has assigned the Fed to conduct the nation’s monetary policy to support the goals of maximum employment, stable prices, and moderate long-term interest rates."(1)
It seems like the two objectives "maximum employment" and "moderate long-term interest rates" are at odd with each other?
At the moment the interest rates are far from moderate (extremely low).
From my understanding this is in order to reach maximum employment?
An interesting Federal Reserve Bank of New York staff report (2) finds that accommodative monetary policies (=QE?) leads to a small decrease in income inequality due to more jobs, but a large increase in wealth inequality.
Wealth inequality is already prevalent in the US (3).
Would changing the objectives of the Feds to:
low unemployment, stable prices, and moderate long-term interest rates
decrease or at least not increase wealth inequality?
(1) What economic goals does the Federal Reserve seek to achieve through its monetary policy?
(2) Monetary Policy and Racial Inequality
(3) Trends in income and wealth inequality

Could the Feds objectives be adjusted to decrease or at least not increase wealth inequality?

Trivially, answer is yes. Congress could just give Fed a mandate for lowering inequality, the same way as congress could pass a law giving Fed mandate to bring world peace or solve world hunger or conduct space exploration. US is sovereign state and Fed is government institution and technically speaking US government can assign Fed whatever mandate it in its infinite wisdom chooses to.

Would changing the objectives of the Feds to: low unemployment, stable prices, and moderate long-term interest rates decrease or at least not increase wealth inequality?

No.  Wealth inequality does not just depend on interest rates. We actually do not yet fully understand what is driving wealth inequality, since data on wealth (as opposed to incomes) is harder to come by and only very recently we became able to reasonably measure it (see Zucman 2019), but there is virtually no doubt that it depends on more than just interest rates.
For example, economic growth tends to reduce wealth inequality between countries but does increase economic inequality within countries (Zucman 2019). Next wealth inequality depends on design of tax system, capital incomes (Saez 2016) and other factors as well. So just keeping moderate interest rates would not reduce inequality or prevent its increase in itself.
Fed could probably do something about wealth inequality, if it would have mandate, but it would not be as simple as keeping interest rates 'moderate'.  However, this would likely often conflict with its other two mandates and thus lead to worse economic performance, and hence the lower inequality might come at a cost of worse economic outcomes.
To illustrate this point, there is some evidence showing loose monetary policy during Great Recession increased relative wealth inequality in the US (Domanski, Scatigna, & Zabai, 2016). However, it is virtually unanimously agreed by macroeconomists that loose monetary policy is necessary during recessions. The reason why Great Depression became "Great Depression" is precisely because Fed decided to follow contractionary monetary policy (see Friedman & Schwartz Monetary History of the US). Great Recession of 2008/9, as bad as it was, was not even a half as bad as Great Depression if we look at metrics such as unemployment (during GD it was $\approx 25\%$ during GR $\approx 10\%$ see Petrosky-Nadeau & Zhang 2016)  or fall of output (see here discussion of drop in US output during GD and here  Fred stats for GR).
Lastly, there is generally a consensus among policy economists that technocratic economic institutions, run not by elected officials but experts and technocrats, such central banks, various regulatory bodies such as Securities and Exchange Commission (SEC) or  Federal Trade Commission (FTC) should deal with technical economic matters and leave matters of redistribution of either wealth or income to elected officials who still have plenty of policy tools to, at least in principle, achieve any level of relative inequality their constituency desires. In principle arbitrary GINI coefficient could be achieved through arbitrary taxation and redistribution (although the same does not hold for absolute welfare and material standards). This being said there is no economic reason why technocrats should not be in charge of inequality this comes down more to moral philosophy and to belief that equity (as opposed to efficiency) related objectives  should be decided democratically.


"Buy a country", expression or possibility? I keep hearing the term, "enough money to buy a country". My question is: Is it realy possible to buy a country or is this just an expression? and if so how would this work since there is no 1 person you could pay for it?

So "Bill Gates has enough money to buy a country." Is this another way of saying he has a lot of money or does this mean he could actualy buy a country if he wished for it. And if its the later then say he did want to do it. How would this work?

Thanks

What do you mean? A country per se cannot be bought. The wealthiest man, Gates, has a net worth of around 67 billion USD (forbes). What could he buy?

GDP

Whatever it the country produces. The poorest country by GDP per capita is Burundi, with a total GDP per capita of around 267 USD, and a population of 10 million. That gives then a total GDP per year of 2.7 billion USD. Gates could easily afford that.

Wealth

We don't have - to my knowledge - reliable wealth data on most developing countries, but the wealth/income ratio is typically around 4-6. Let's assume the maximum, 6. That would give the people of Burundi 13 billion USD, still affordable.

Public Assets

Let's pick a random country, switzerland. They have public assets worth 200 billion USD. Too much for Gates to afford. But for a smaller country, he could surely buy it out.

The answer is somewhat unsatisfactory. Why? Because the question is. In the end, before asking can xyz really happen, you should ask what is xyz  and what do I mean by it?

What else is there?

I'm not aware of a country where the people are still counted as property, so you most likely can't buy them.

Perhaps you could buy all the land? There are many small islands (potentially for sale) that would grant you independence. Some people (mostly rich and eccentric) own them, which means I presume that they bought those countries at some point. So, it turns out,

  You can buy a country

but you can't buy the people. !Viva la revoluçion!


According to North, Wallis, and Weingast (NWW), which states/societies have successfully made the transition to open access? Weingast (2016) writes:

  The NWW framework redefines the process of economic and political development as the transition from a limited access order to an open access order. The transition is a difficult process, and NWW argue that only two or two and a half dozen states have successfully completed it.

Earlier, NWW (2009) had written:

  Perhaps 25 countries and 15 percent of the world’s population live in open access societies today

Have NWW ever explicitly stated what specifically these "two or two and a half dozen states" or "[p]erhaps 25 countries" are?

In NWW (2009), they have three subchapters (6.5, 6.6, and 6.7) specifically discussing the transition to open access in Britain, France, and the US. So these are three. What are the other 20+ states that in their opinion have also successfully made this transition?

In NWW (2006) they write "In the twentieth century Taiwan, South Korea, Ireland, and Spain appear to have made very rapid transitions [to open access]."
Most of the 37 countries in the OECD would seem to have made the transition, with exceptions being Columbia, Hungary, Mexico, and Turkey. Several Balkan and the Baltic countries may not make the grade either. Perhaps using a combination of Pritchett's (2021) 'stock' version of Polity IV and the WB Ease of Doing Business data would provide a useful measure of open access to political and economic organizations. (Although the latter seems to be increasingly discredited).


Why is perfect price inelasticity of demand not considered an exception to the law of demand? Assume a case of perfect price inelasticity of demand.

In such a case,

  PED = 0

The quantity demanded does not respond to changes in price, i.e. it remains constant, even when price increases or decreases (instead of falling or rising, as it should if it conformed to the inverse relation defined by the law of demand).

Thus, shouldn't perfect price inelasticity also be considered as an exception to the law of demand, just as Giffen goods and Veblen goods are?

Because although some goods have perfect inelasticity over some interval, they are not perfectly inelastic over the whole demand curve - over the rest of the curve, quantity and demand will be strictly inversely related. And the law of demand doesn't have a "strictly" in there. Price and quantity are inversely related, but not strictly so, which (in the mathematical sense) means that parts of the demand curve are allowed to be perfectly inelastic.


Does Abatement Cost Mean Cost of Reducing Emissions with Output Held Constant? In the economics of pollution control, frequent reference is made to 'abatement cost' and/or 'marginal abatement cost'.  Is it normally implicit in the use of these terms in economics that output is held constant?  In other words, that the cost referred to is the cost of reducing emissions while producing the same output?

Common & Stagl (1) offer an explanation of abatement cost which explicitly states that abatement may be achieved by a reduction in the activity producing the emissions.  However, most presentations of abatement cost that I have seen do not make such a statement.  So would that perhaps be a non-standard usage from an ecological economics perspective?

Please note this is a question about correct or normal usage of 'abatement cost'.  There is of course a real issue about whether we should be producing and consuming less so as to reduce damage to the environment, but I'm not asking about that here.

Reference:
(1) Common M & Stagl S (2005) Ecological Economics: An Introduction Cambridge University Press  p 415

No, there's no assumption that output is constant.

Indeed, in most cases, it's expected that output will change, if only a little.

For example, there are abatement costs that involve a one-off increase in output which brings about a long-term decrease in output, such as insulating buildings to abate greenhouse-gas emissions from fossil-fuel powered heating.

Let's take the case of an Australian dwelling being insulated late in the year, during the start of summer, in November 2014 (I'll take the accouting year to be the same as the calendar year, rolling over on 1 Jan). So for 2014, we have had full heating costs from the winter that took place May-August, as well as the manufacture and installation of the insulation materials; so 2014 sees an increase in output over 2013. But in 2015, that insulation won't be manufactured or installed, and the dwelling's heating demand will be lower, so 2015's output is below that of both 2014 and 2013.

To produce output-constant costs would require putting the abatement measures through a macroeconomic model, as part of their cost-estimation. Abatement cost calculations are messy and uncertain enough as it is (before we even get onto the problems with marginal abatement cost curves, one of their more common presentations), without adding a whole extra layer of messy uncertainty that is macroeconomic modelling.


Indifference curves passing thru few points Tommy Twit’s mother measures the departure of any bundle from her favorite bundle for Tommy by the sum of the absolute values of the differences. Her favorite bundle for Tommy is (2, 7), that is, 2 cookies and 7 glasses of milk. Tommy’s mother’s indifference curve that passes through the point (c, m) = (4, 5) also passes through

a.
the points (4, 7), (2, 5), and (2, 9).

b.
the point (2, 7).

c.
the points (2, 3), (6, 7), and (4, 9).

d.
the point (6, 3).

e.
None of the above.

How to solve this question? I thought that it is enough to find a line passing through two points given however then the equation would be $y=9-x$ however the points given does not fit to the equation. Correct answer given in a questionbank is C. I have no additional info regarding this question and i have to admit yes it is badly stated.

The first sentence means that Tommy's mother's utility function over a bundle $(x,y)$ equals
\begin{equation*}
u(2,7)-u(x,y)=|x-2|+|y-7|
\end{equation*}
since she measures the disutility of this bundle with respect to the most preferred one by the "sum of the absolute values of the differences".

Therefore the utility that she associates with the point $(4,5)$ equals
\begin{equation*}
u(4,5)=u(2,7)-(2+2)=u(2,7)-4
\end{equation*}

You are asked to find the indifference curve that passes through the point $(4,5)$, i.e. the set of bundles $(x,y)$ that satisfy
\begin{equation*}
u(x,y)=u(4,5)
\end{equation*}
which you can write
\begin{equation*}
u(2,7)-u(x,y)=u(2,7)-u(4,5)=4
\end{equation*}

The question is therefore: which of the options a), b), c), d) (if any) contain only bundles $(x,y)$ such that $u(2,7)-u(x,y)=4$? You simply have to compute $u(2,7)-u(x,y)$ for all the proposed bundles, given the formula above, and check whether the value equals 4 or not.


Effect of information on stock indices The rules for including a stock in indices such as S&P 500 are common knowledge, so everyone can know when e.g. company B is going to enter the index instead of company A. Since ETFs and mutual funds tracking the index have to buy shares of B and sell shares of A, this can potentially used by speculators who would try to quickly buy B and sell it to the ETFs in a high price, while buying A in a low price from the ETFs. Does such kind of speculation have any effect on the stock prices?

Specifically: Suppose someone invents a new index, X&Y 500, in which the identity of the companies is kept secret and revealed only to issuers of ETFs and mutual funds. All other things being equal (e.g. the companies in both indices are equally strong, have the same business potential, the volume of ETFs of both indices is the same, etc.), will the secret index X&Y 500 perform better than the revealed index S&P 500?

EDIT: To make the question even more focused, assume that there is no way to know in advance which stocks are going to enter/exit S&P 500 (e.g. these stocks are selected at random). So the difference between S&P 500 and X&Y 500 is that the stocks in the former are revealed to all traders at the same time, while the stocks in the latter are revealed only to ETF issuers.

If you believe the efficient market hypothesis, then the answer is no;

At the moment relevant information (say, which allow the company to be added to the index reveal, the stock price would automatically reflect the price as if it was already added to the index, as otherwise there would be arbitrage closable by buying the stock at this moment and selling it when the ETFs are getting in.

In practice, I've tried it a few times myself but it seems that in general the market already takes future ETF investments into pricing quite well.


Difference between a 3-months UK nominal spot rate and a 3-months UK treasury bill discount rate? I am trying to collect data I could use for calibration of a short-rate modeling process, so I need data which represents the historical short-rates.

On the Bank of England webpage I came across the historical Government liability curve data, and also the 3-months UK treasury bills discount rates.

It turns out they are not the same. For example, on the 31 May 2017 the UK nominal 3-month spot rate was 0.04, and the 3-months UK treasury bill discount rate was 0.0575. Also, in the 3-months UK nominal spot rate table, values of 3-months spots are actually mostly not given.

I don't understand what is the difference between these two values, and which ones should I use for my historical data?

Many thanks for any insights on this.

They are based on completely different assets.

Gilts:

As this document states:

the government liability nominal yield curves are derived from UK gilt prices and General Collateral (GC) repo rates.

Later on, the same document defines:

A conventional gilt is a guarantee by the Government to pay the holder of the gilt a fixed cash payment (coupon) every six months until the maturity date, at which point the holder receives the final coupon payment and the principal.

These assets are usually long term. As this page states:

In recent years the Government has concentrated issuance of conventional gilts around the 5-, 10- and 30-year maturity areas, but in May 2005 the DMO issued a new 50-year maturity conventional gilt. In June 2013, following market consultation the DMO issued a new 55 year maturity conventional gilt.

Meanwhile, the document referred earlier defines "General Collateral (GC) repo rates" as:

General collateral (GC) repo rates refer to the rates for repurchase a
greements in which any gilt may be used as
collateral.  Hence, GC repo rates should in principle be close to true risk-
free rates.  Repo contracts are actively traded for maturities out to one year;  the rates prevailing on these contracts are very similar to
the yields on comparable maturity conventional gilts.

Notice the phrase in bold. The rates are similar to comparable (e.g. 3-month T-Bills), but not identical. Unfortunately, they do not state why.

3-months T-Bills:

According to Bank of England definitions, the "Treasury bill tender 3 month (91 days) bills" is:

Treasury Bills are bearer Government Securities representing a charge on the Consolidated Fund of the UK issued in minimum denominations of £5,000 at a discount to their face value for any period not exceeding one year. Although they are usually issued for 3 month (91 days), on occasion they have been issued for 28 days, 63 days and 182 days. They are issued:

by allotment to the highest bidder at a weekly (Friday) tender to a range of counterparties;
in response to an invitation from the Debt Management Office to a range of counterparties;
at any time to Government departments (non-marketable bills only).

Regarding why they have less data available, the same article points out that:

The secondary market in Treasury bills has in recent years become illiquid and representative rates are no longer obtainable other than those for the most recently issued 91 day bills. The rates shown are the average rates of discount at the weekly tender for 91 day bills.

Finally, regarding to which one to use, I would be definitively inclined to use the data related to the yield curve (gilts). This, as indicated above, are traded daily in the secondary market. Thus, data is more extensive, and perhaps more "reliable".


How accurate is duality? In economic theory we know that with the use of some calculus, Hotellings Lemma and Sheppards lemma we can derive a given firms supply function and in term its Profit function.

With data of a given firms costs, can we in fact get an accurate estimate of its profit function and supply function?

Let me focus on the use of duality theory in demand analysis (as this is what I'm most familiar with).
Direct approach
Usually, in order to obtain a demand system (which you can then estimate) you need to take the following steps.

specify a utility function $u(x_1, \ldots, x_n)$.
maximize this with respect to a budget constraint $\sum_i p_i x_i \le m$. .
Obtain a closed form solution for $x_i$ as a function of all prices $(p_1,\ldots, p_n)$ and income $m$.
Estimate these functions.

Step 3 is the trickiest part as usually no closed form solutions are possible. To see this, notice that the first order conditions give the following system:
$$
\frac{\partial u(x_1, \ldots, x_n)}{\partial x_n} = p_i\,\, \lambda,\\
\sum_i p_i x_i = m.
$$
Solving for $\lambda$ we have:
$$
\dfrac{\dfrac{\partial u}{\partial x_i}}{\sum_j \dfrac{\partial u}{\partial p_j}} = \frac{p_i}{m}
$$
This gives the (normalized) prices on the right hand side as a function of the quantities (so the inverse demand functions). To obtain a closed form solution of the quantities in terms of the functions, this system needs to be inverted. Except in some particular cases (e.g. Cobb-Douglas or CES) we do not know how to do this.
Dual approach
The dual approach starts from a specification of the expenditure function and uses known duality results to obtain a closed form expression for the demand functions. It takes the following steps:

Specify an expenditure function $e(p_1, \ldots, p_n,u)$.
Use Shephard's lemma to obtain the Hicksian demand function $h_i(p_1,\ldots, p_n, u)$.
Invert $e(p_1, \ldots, p_n, u)$ with respect to $u$ to get the indirect utility function $v(p_1, \ldots, p_n, u)$.
substitute $v(p_1, \ldots, p_n, u)$ in $h(p_1, \ldots, p_n, u)$ to get the Marshallian demands $x_i(p_1, \ldots, p_n, m)$.

As an exemple, consider the widely used Almost Ideal Demand System specification of Deaton & Muellbauer
Start from the following (flexible) specification for the expenditure function.
$$
\ln e(p,u) = \alpha_0 + \sum_i \alpha_i \ln(p_i) + \sum_{i,j}\frac{1}{2}\gamma_{i,j} \ln(p_i) \ln(p_j) + u \prod_i p_i^{\beta_i}
$$
We impose $\gamma_{i,j} = \gamma_{j,i}$, and by homogeneity of degree 1 we have that $\sum_i \alpha_i = 1$ and $\sum_{i = 1}^n \gamma_{i,j} = 1$ and $\sum_{i} \beta_i = 0$.
First we can take the derivative $\frac{\partial \ln e(p,u)}{\partial \ln p_i}$ to get the demand share equations. Shephard's lemma gives:
$$
\frac{\partial \ln e(p,u)}{\partial \ln p_i} = \frac{p_i h_i(p,u)}{e(p,u)} = \alpha_i + \sum_j \frac{1}{2}\gamma_{i,j} \ln(p_j) + u \beta_0 \beta_i \prod_i p_i^{\beta_i}
$$
Here $h_i(p,u)$ is the Hicksian demand for good $i$.
Writing by $v(p,m)$ the indirect utility function, we know by duality between utility maximisation and expenditure minimisation that:
$$
m = e(p,v(p,m)) \text{ or } u = v(p,e(p,u)).
$$
Using this, we can invert the expenditure function to obtain the indirect utility function.
$$
v(p,m) = \frac{\ln m - \alpha_0 - \sum_j \alpha_j \ln(p_j) - \sum_{i,j}\frac{1}{2} \gamma_{i,j} \ln(p_i) \ln(p_j)}{\beta_0 \prod_i p_i^{\beta_i}}
$$
Also by duality, if $x(p,m)$ is the Marshallian demand function then:
$$
x_i(p,m) = h_i(p,v(p,m)).
$$
So we can substitute $v(p,m)$ into $h_i(p,u)$ to get the shares as a function of prices and income.
$$
\begin{align*}
s_i(p,m) &= \frac{p_i x(p,m)}{m} = \alpha_i + \sum_j \frac{1}{2}\gamma_{i,j} \ln(p_j) + \beta_i \left(\ln m - \alpha_0 - \sum_j \alpha_j \ln(p_j) - \frac{1}{2}\sum_{i,j} \gamma_{i,j} \ln(p_i) \ln(p_j)\right),\\
&= \alpha_i + \sum_j \frac{1}{2}\gamma_{i,j} \ln(p_j) + \beta_i \ln(m/P).
\end{align*}
$$
where:
$$
P = \alpha_0 + \sum_j \alpha_j \ln(p_j) + \sum_{i,j} \frac{1}{2}\gamma_{i,j} \ln(p_i)\ln(p_j).
$$
This is the Almost Ideal Demand System. Conditional on $P$, shares are linear in the log of income and log of prices. The symmetry and homogeneity restrictions immediately translate to conditions on the coefficients of this system.


Where are the payments for export in the balance of payment? I know that when we sell some goods abroad, we credit Goods&Services part within Trade balance, which is a part of Current Account.

What part of the Financial Account is debited with the sum received for the exported goods?

The physical part of trade in goods and services is recorded in the Current Account and the payment (with financial assets) part of the transaction is recorded in the Financial Account. The Balance of Payments should be 0 after you sum up the Current Account balance, the Capital Account and the Financial Account balances. The trade in goods and services is recorded in Current Accounts. For instance, exports are credited and imports are debited.


Insect farming as future of protein nutrition: reality check Currently, about 2bn people consume insects, so there must be a scaled industry already as well.

Then, you can buy cricket powder at roughly $100/kg.

Now my concern is:

if this is already a common nutrition source, why the price? (could not imagine, those 2bn people pay that)
nevertheless insect farming wherever it takes involves lot of manual labour

In my understanding, a future source of food should match the following criteria:

sustainable (OK)
cheap (not clear)
scalable through automation (I think this is currently very limited)

Compared to a meat brewery, if they will mature, seems easier to scale, even if entrypoint is harder.

So why is the price currently so high and how exactly are these insects will become the future of food (media excitement put aside) - is a realistic criteria market turnover?

Currently, the problem lies in the genetic selection to make insects suitable for mass processing.

Let's compare this to chicken farming

Human society already select chicken that will grow lots of meat for many years
There are machinery available to "process" the chicken
There are existing demands and supply chain.
Currently chicken is cheap

In industrial scale, it is all about ease of processing.  Currently, insects like crickets is not a good competing candidate. However, it is just a matter of time for the food scientist to discover a suitable insect.


Exogenous variables and money What are the exogenous variables that drive demand for and supply of money? Are there variables in common between the two? I think I'm getting caught up with interest rates, as adjusted by the Feds vs the natural return from investment etc.
Thanks in advance for any help!

The three critical exogenous variables that drives the demand for and supply of money, according to Investopedia, are liquidity, investment, and consumption.

According to theory, liquidity is determined by the size and velocity of the money supply. The levels of investing and consumption are determined by the marginal decisions of individual actors.

All of this is depicted in the IS-LM model which stands for "investment-savings" (IS) and "liquidity preference-money supply" (LM).   This was used to explain the economics ideas by John Maynard Keynes in the 1930s.  Developed by economist John Hicks in 1937 after Dr. Keynes published his book "The General Theory of Employment, Interest and Money" (1936).


If a CDS is x%, why does this mean $(1 - x)\%$ probability of default? At 11:52, Tim Bennett says:

  Well let's have a look at
  11:52
  some prices. Currently the cost of
  11:57
  insuring Greek debt is in excess of
  12:02
  $\color{green}{2,000}$ basis points. Another way of
  12:07
  looking at that is that you are paying as a
  12:09
  premium annually $1/5$th of the value
  12:12
  of the debt in question. So another way
  12:16
  of looking at that is: the market is
  12:19
  effectively giving the chance of Greeks
  12:20
  going bust within five years over $\color{red}{80\%}$
  probability.

Doesn't the cost a Credit Default Swap (CDS) for Greek debt is $\color{green}{20\% (= 2000}$ bp), entail that the chance of default by Greece is also 20%? Why  $\color{red}{80\%}$?

Note that the 20% annual premium would imply a 20% annual default probability. Tim Bennett is then talking about the probability of default within five years.

He might have thought that
$$
1 - Prob(\text{no default for five years running}) = 1 - (1 - 0.2)^5 > 0.8
$$
but this is not true as
$$
1 - (1 - 0.2)^5 \approx 0.67
$$


Using dependent variable's and exogenous variables' lags as instruments in 2SLS Suppose we have the following structural equations:
$$y=\beta_0+\beta_1x+\beta_2z_z+\beta_3z_3+\epsilon,$$
where $x$ is the endogenous variable and $z_1,z_2$ are exogenous variables. In the literature, as well as in software packages (ivreg in STATA), I find that it is quite common to add dependent variable's as well as lagged exogenous variables as intruments in the first stage of 2SLS (to capture exogenous variation of the endogenous variable). In our case, we can consider $y_{t-1}, x_{t-1}, x_{t-k}$ as instruments for $x$. Is this legit and what is the rational behind this? Also, please provide some resources to read more about this. Thanks!

Is this legit and what is the rational behind this?

Yes you will find this even as a recommendation in many textbooks (e.g. see Romer Advanced Macroeconomics pp 376)  so it is legit although with a caveat.
A good instrument should be correlated with the endogenous variable and be able to through it exert an effect on dependent variable. Well lags are more often than not highly correlated with the contemporaneous observation of the same variable.
Next, instruments should not be correlated with residuals and for lags this will often hold (but not always) in economics.  This is because in many cases when the residual reflects new information learned by people between $t$ and $t-1$, economic theory simply often tells us that any variable that is known as of time $t − 1$ is uncorrelated with the residual.
However, this being said lagged instruments can still turn out to be weak, or violate some of the other assumptions of IV (for overview of all assumptions required for IV see for example Verbeek, a Guide to Modern Econometrics or Angrist & Pischke Mostly Harmless Econometrics), and the above might not hold generally for any economic relationship. So these are no silver bullet, but they often do make sense in economics. Nonetheless, there is a criticism of their overuse in economics (see for example Wang & Bellemare 2019). However, this is to my best understanding not because they would not be legitimate instruments but rather many practitioners just  apply them without even bothering to check if other conditions that good instrument should satisfy are actually really satisfied.


How government borrowing from central bank increases money supply in economy? Yes, public finance by government may lead to increase in money supply in economy. But, if govt borrows money from central bank, less amount of money is left with central bank to lend it to banks and hence less money supply in economy.
I am unable to figure it out.

Central banks can create money 'out of nothing'. So for starters there isn't 'less amount' of money left with the central bank. The amount of money at the central bank is 'infinite'.
So it's not because the CB lends X amount of money to the government, that the CB has X amount less money to lend to the banks, the supply of money is not constrained...
Off course, creating too much money and monetizing debt can have negative consequences for sure (for example hyperinflation in extreme cases), but that's another discussion.
See also here for more info about quantitative easing: https://www.youtube.com/watch?v=4TihoBfdCe8 and here: http://www.investopedia.com/terms/q/quantitative-easing.asp

Edit: comment from Energy numbers: strictly speaking government borrowing money from central banks doesn't increase the money supply, it only increases when the government spends the borrowed money.


Why are interest rates so high in Russia? In Russia we currently have 11% of Central Bank's interest rate and you can get credit in commercial bank for about 25% in year. Why are interest rates so high?

I think the answer to your question does not require reference to economic theory as you are trying to understand why Russians cannot borrow at low rates. The prevailing high rates are not there for suppressing business activity, etc. This is something to do with the risk appetite of Russian commercial banks when dealing with domestic businesses.

Why are Russians facing rates as high as 25% when the base rate is 9%?

Central Bank's current base rate is 9%, also called repo rate. This rate is the main monetary tool used by CB to influence the interbank interest rates and the interest rates for loans, mortgages and savings. As you can see, the CB rate is low, but the commercial banks are adding huge premium (here it is 16%) to the base rate when lending to domestic businesses. Perhaps, they may face high default risks, political risk, high inflation, exchange rate risk, etc.

As a side note, this is a typical characteristic of a transition economy, that's said, Russians will face relatively high interest rates till they gain 'developed' status.


Good source for marginal propensity to consume by country? Is there a good data source that aggregates the MPCs of various countries?

Thanks.

You may need to do some math but the OECD database does have the data that you need to construct MPC by country.     As a reminder MPC can be calculated as the change in consumption (ΔC) divided by the change in income (ΔY).

For consumption the OECD data series you would need is "Household spending"  https://data.oecd.org/hha/household-spending.htm#indicator-chart.

For income the OECD data series is called "Household disposable income"
https://data.oecd.org/hha/household-disposable-income.htm#indicator-chart

Download the available data and calculate the growth rates of each measure then solve for MPC  and you should have it.   If you have trouble with the data download contact the OECD for assistance.


Capital Asset Pricing Modeling for Consumption Suppose Asset $A$ has a variance of 7 and its returns are negatively correlated with consumption, while Asset $B$ has a variance of 3 and its returns are uncorrelated with consumption.

According to the Consumption CAPM, which asset should yield the higher return?

I believe it is Asset $A$ because CAPM asserts that you should choose an asset that is negatively correlated with consumption.

What do you guys think about my answer?

I guess the question is : which asset would yield the higher risk premium or expected return?

Risk premium depends indeed on the intrinsic characteristics of the asset, and on the pricing kernel, in particular the covariance between the pricing kernel (which is proportional to marginal utility) and the asset return. Therefor the risk premium will depend on the utility function you specify. But the general idea is that an asset that pays high when consumption is high will have a lower price and then a higher return to compensate for that risk. Under complete market, the general formula is :
\begin{equation}
E(R^{e}_{t+1}) = -R_f\cdot cov(m, R^e_{t+1})
\end{equation}

where $R^e_{t+1}$ is the excess return, $R_f$ the risk-free rate, and $m$ the stochastic discount factor. $m$ will depend on the utility you specify but will be proportional to the marginal utility. Because of the (generally assumed) concavity of utility function, $m$ will be low when consumption is high and high when consumption is low.

In your example, the expected excess return of asset B would be 0, otherwise stated the expected return of asset B would be the risk-free rate because its return is uncorrelated with consumption.

Asset A pays high when consumption is low, so when marginal utility is high, so the risk premium will be lower than the risk-free rate. The main idea is that since this asset can be use as insurance against variation in consumption, agents will want to hold it, so its price will be higher and then its return lower.

So you were almost right, asset A will have a higher price than B, but a lower expected return.


Regression Optimization problem under constraints To estimate a simple linear regression:
$$ y = \beta_0 + \beta_1 x + \epsilon $$
I have the assumptions that a researcher $A$ can only sample individuals with a value $y < y^A$. Similarly, a researcher $B$ can sample individuals with a value $y <y^B$, with $y^B < y^A$. I also know that $\beta_1 < 0$.

Are the estimates from the researchers $A$, $B$ going to be biased?
If so, which one is likely to be more biased?
How can I illustrate that graphically?

What I have tried so far, is to assume that $y^A = (\hat{\beta_0} + \hat{\beta_1}x)^A$ and then I tried to derive the OLS for this model instead but I stumble upon calculations, i.e.
$$  \partial{(SSR)}/\partial{\beta_0}  = -2A \sum{\left( y_i - (\beta_0 + \beta_1 x_i)^A\right) \left(  \beta_0 + \beta_1 x_i\right)^{A-1}} = 0$$
How do I get along from here? I have some intuition that I should use a logarithmic approach?

The situation is given in the following picture

The black line is the true conditional mean $E(y|x)$. If we truncate the data, all observations above the truncation $Y^A$ are not observed.
For low values of $x$, we will observe (on average) lower values of $y$ than we would without the truncation. As such, when $x$ is low, the observed conditional mean function (in blue) will be lower than the true one. If you fit a linear function through the observed points (say in red), you will therefore fit a linear function approximating the blue one. This will be a function with a flatter slope (compared to the true conditional mean in black).
The following is not exact, but only gives an idea how I would approach the problem analytically.
Assume that the true data generating process be given by:
$$
y_i = \beta_0 - \beta_1 x_i + \varepsilon_i.
$$
Where, as usual, $E(\varepsilon_i) = 0$ and $E(\varepsilon|x_i) = 0$. The conditional mean function is then equal to:
$$
E(y_i|x_i) = \beta_0 - \beta_1 x_i + E(\varepsilon_i|x_i) = \beta_0 - \beta_1 x_i.
$$
Now let $z_i$ be the random variable equal to 1 iff observation $i$ is not truncated, i.e. when
$$
 \beta_0 - \beta_1 x_i + \varepsilon_i < Y^A.
$$
If $i$ is not observed, i.e. truncated, we have $z_i = 0$.
Then the observed conditional mean equals:
$$
E(y_i|x_i,z_i=1) = \beta_0 - \beta_1 x_i + E(\varepsilon_i|x_i, z_i = 1).
$$
The last term is given by:
$$
E(\varepsilon_i|x_i, z_i = 1) = E(\varepsilon_i|x_i, \varepsilon_i < Y^A - \beta_0 +  \beta_1 x_i)
$$
This last term, which is a function of $x_i$ is negative (as $\varepsilon_i$ is truncated from above and the mean of the untrunctated $\varepsilon$ is zero). Define:
$$
E(\varepsilon_i|x_i,\varepsilon_i < Y^A - \alpha_0 +  \alpha_1 x_i)  = g(x_i).
$$
we have that $g(x_i) < 0$ and in general, we would expect that $g'(x_i) > 0$, because the restriction is less binding if $x_i$ becomes bigger (This however is probably not always the case, as $g$ depends on the shape of the joint distribution of $\varepsilon_i$ and $x_i$.)
Then we have:
$$
E(y_i|x_i, z_i = 1) = \alpha_0 + \beta_1 x_i + g(x_i),
$$
This is the blue curve in the picture.
The slope of this line equals:
$$
\frac{\partial E(y_i|x_i, z_i = 1)}{\partial x_i} = -\beta_1 + g'(x_i)
$$
The right hand side of the first equation is bigger than $-\beta_1$ (so the slope is flatter).
Notice that in general, the conditional mean will alsono longer be a linear function of $x_i$, so there will also be a specification bias. This also makes it not trivial to determine what exactly the bias will be from fitting a linear function.
Lowering the value of $Y^A$ will lead to a larger bias (more negative $g(x_i)$) and probably also to a flatter slope of the estimated regression. I hope this is intuitive from the picture above.


The process of printed money reaching the government? I saw a link that suggested that when the fed prints money, this money is actually lent to the government in the form of bonds, not given. This, despite the fact that the Fed is (loosely) associated with the government.

My question is...

Is this correct?
If so, how are the interest rates determined?

1) The phrasing you use is somewhat non-standard, but it seems close to the correct view.

The U.S. Treasury borrows by issuing bonds. What people loosely call “printing money” (a badly defined phrase) is that the Federal Reserve buys those bonds from their owners. The original owners of the bonds “lent” the Treasury the money, and the Fed just takes the loan of their hands. The Fed pays for the bond by creating a deposit at the seller’s bank (the central bank is a bank which takes deposits from private banks), and that deposit is considered to be “money” (technically, part of the monetary base).

The Treasury owns the common equity of the Federal Reserve, so to a certain extent, it is one arm of the government dealing with another.

There are plenty of questions on here that discuss “quantitative easing” and give longer explanations.

2) The Fed buys and sells bonds in the market, so it is a market rate.


Why politicians choose Mega Projects in developing countries? kindly forgive me if this doesn't belong here. I just thought probably it's suited here.

Why do politicians choose mega projects in developing countries instead of spending more on health and education?

Also, are there any noted academics who work in this area.

Kindly enlighten.

You are looking for the political economy literature on government expenditures. That is a massive literature. A starting point may be given here.

A summary of all possible reasons for so-called white elephants is difficult without a more specific question. Are you interested in corruption, asymmetric information, institutional explanations, political preferences...?


Why was protectionism considered bad in the great depression? its said that "there is all-but-universal agreement that the adoption of restrictive trade policies was destructive and counterproductive and that similarly succumbing to protectionism in our current slump should be avoided at all cost."

However, doesn't that depend on your net exports? so if more is leaking from your economy, than is being injected, protectionism is a good strategy, right?

Net exports aren't in and of themselves a bad thing; they should just be a transitory phenomenon. A prolonged export imbalance should just lead to an exchange rate adjustment which fixes the imbalance.

Protectionism on the whole, in general, leaves all sides worse off. David Ricardo documented it very well; and it wouldn't surprise me if there were proverbs in all the major ancient civilisations to the same effect.

There are exceptions: for example, infant industries typically need protection during their vulnerable early years, so that they can reach sufficient maturity that they can thrive under international competition.

However, that's different to the general protectionism that does get proposed at times of deep slump - the Long Depression, the Great Depression, and the current (2008-now) slump: then, it's one of the (socially and economically) worst options, but does appeal to the masses when they're desperate for an "other" to blame, and for easy answers to complex questions.


Where can I find real-time indicators of economic activity? In this paper, they are using Canadian debit card dataset. I am not sure where to get such a dataset.

http://www.cirano.qc.ca/pdf/publication/2009s-23.pdf

My broad question is what kind of indicator can I use that indicates real-time economic activity of the people? Something that indicates how much people are buying on an hourly basis for an example. I am willing to look at unconventional datasets or willing to scrape information from scratch.

I thought about using Amazon review timestamps for example, but I know want to when people are buying something. Specially over the United States or smaller.

The projects developed by Alberto Cavallo and Roberto Rigobon could be a source of inspiation.

The Billion Prices Project is an academic initiative that uses prices collected from hundreds of online retailers around the world on a daily basis to conduct economic research. This page shows their most recent research leveraging high-frequency price data, as well as the US daily inflation index (updated monthly).

Here are the datasets on Online Micro Price Data, Global Retailers Data...


Are profits procyclical? This is somewhat related, but distinct from Cyclicality of Markups

Basically, I'm looking for papers on whether firms profits are (on average) procyclical or not, and I appreciate theoretical, but look mainly for empirical papers.

My reading is yes, it is procyclical in levels and margins.

  This paper uses industry and firm data to look at price cost mark-ups
  and firm profit margins in U.K. manufacturing and services. In
  particular it examines how they behave over the business cycle. It has
  two main findings. First, the estimated average mark-ups and the
  profit margin results both suggest that there is imperfect competition
  in manufacturing and services. Second, mark-ups are pro-cyclical, as
  are profit margins even after allowing for movements in their standard
  determinants. This suggests that price pressures may increase during
  recovery periods and decrease during recessions. One possible
  explanation for this is Kreps and Scheinkman's argument that the
  pro-cyclicality of capacity constraints means that firms move between
  Cournot and Bertrand competition over the cycle. The finding that
  mark-ups are pro-cyclical also raises doubts about macroeconomic
  models that assume that demand shocks may affect employment via
  counter-cyclical mark-ups.

The Cyclicality of Mark-Ups and Profit Margins: Some Evidence for Manufacturing and Services

  In this paper, we assess the cyclicality of mark-ups and profit
  margins within the United Kingdom, at both the aggregate and industry
  level. We find that the private sector labour share moves
  countercyclically, suggesting that the aggregate mark-up moves
  procyclically. This result survives when we consider more
  sophisticated measures of the mark-up. And this result is also
  supported by industry-level data. We find that the aggregate market
  sector profit share moves procyclically and that the cyclical
  behaviour of profit margins is largely homogenous across industries.
  Nevertheless, there is some evidence that margins moved against the
  cycle in the late 1990s, starting to fall in 1997, whereas GDP growth
  did not peak until 2000. In tandem with these cyclical movements, we
  also find that the market sector profit share has trended upwards
  since 1970, in contrast to the aggregate mark-up, which fell over the
  same period.

The Cyclicality of Mark-Ups and Profit Margins for the United Kingdom: Some New Evidence

  Modeling cash flows separately from aggregate consumption is crucial
  since corporate cash flows have historically been far more volatile
  and sensitive to economic shocks than has aggregate consumption. For
  example, corporate earnings have been more than ten times as volatile
  as consumption growth during the post-war period. Similarly, while
  aggregate consumption declined nearly 10 percent during the early
  stages of the Great Depression, aggregate corporate earnings were
  completely obliterated as they fell more than 103 percent. In addition
  to being more volatile, corporate cash flows are also highly
  correlated with aggregate consumption because of their strong
  procyclical behavior. To provide specifics, during the 1929 to 2001
  period the volatility of earnings growth was 29.5 percent, while the
  correlation between per capita real consumption and earning growth was
  68.7 percent.

  Intuitively, the reason for the extreme volatility and procyclicality
  of corporate earnings is that stockholders are residual claimants to
  corporate cash flows. Thus, the compensation of workers is a senior
  claim to cash flows. In other words, labor contracts provide workers
  with some degree of insurance against business cycle risk. These
  contracts make the fraction of labor income in output (or consumption)
  countercyclical, while the fraction of earnings in output is
  procyclical. Gomme and Greenwood (1995) document that these
  business-cycle-related changes in labor income and earnings can be
  found in many countries.
  CORPORATE EARNINGS AND THE EQUITY PREMIUM

Finally,
On the cyclical allocation of risk P.117 shows that Labor’s share of income (in Australia, Austria, Britain, Canada, France, Germany, Japan, and the USA) is negatively contemporaneously correlated with the seasonal component of aggregate income, suggesting that when aggregate income is high profit margins are high.


Is Dominique Strauss-Khan really "the best economist of France"? Dominique Strauss-Khan (often called DSK) is a French politician, from the Socialist Party. He has been Minister of Economics and managing director of the International Monetary Fund (IMF) from 2007 to 2011. He may have been the candidate for the Socialist Party during the election of the French President in 2012, and is assumed to have good chances to win. He was lecturer in economics for some years in several French universities.

French often nickname him as "the best economist of France" newspapers (e.g. here) . To be simple:

Is DSK the best economics of France?

This question is certainly opinion-based, but economics is, among other things, the science of evaluation and of utility, I hope there may exist some metrics (directing the IMF may be one of these)  that allows to estimate his importance in the current economic world so the question may be understood as

In which perspective can DSK be considered as the best economist of France? Under which criteria?

PS: I didn't know exactly how to tag this question. I used macroeconomics because of his position at IMF and his involvement in the Greek crisis.

Jean Tirole is a French economist, with a degree from a French school, working at a French school, and as of the June 2015 the tenth most cited living economist as measured by Repec with 13,649 citations. That's about the same citation count as an entire top 100 ranked department. Everyone else in the top 10 works in an American institution and was born in the USA (8) or Russia (1). Dominique Strauss-Khan doesn't even make the top 5 percent list.


Any information on a toy economy with 3 types of agents in it I was thinking about a theoretical economy where there are 3 types of roles for the agents. They can be :

workers : produce good A
criminals : steal good A
cops : protects good A

without going into details, are they any theories around this type of economy and the different types of equilibrium that can be achieved, using different characteristics for agents, different rules etc...

This idea came from the fact that raising productivity could have perverse effects (raise criminality in this case) given certain conditions.

Also, do you have any tips on researching among existing economic theories for something that will describe an idea that you might have,

Becker has a very widely cited paper about crime that generally defines the literature, here.

To examine your proposal, increases in productivity generally lead to higher wages in the legal sector, but could easily increase crime rates if they disproportionately increased the returns to crime.

No agent modeling or network theory is needed for this to an accepted idea in the literature, but you're welcome to explore it if you think the consequences are somehow divergent from what I've outlined here! Furthermore, the actual task to -verify- his theory is very difficult. To search "the literature", I would search within the body of papers citing this particular Becker paper.


Why is airbnb more expensive than priceline? Some might say I have an addiction to Priceline Name Your Own Price, however, what I can tell you is that NYOP rates for 2.5* and 3* hotels are always better than the room options offered through airbnb.

What I cannot understand is why do so many people believe otherwise, claiming that going with airbnb is cheaper?

Likewise, why the landlords are asking for such high rates all the while NYOP and even published Express Deals are often half the price, yet include gyms / pools / breakfasts for the whole family.

It should not be at all surprising that different people choose different offers: the short-stay accommodation market (let's say 1-30 nights) is characterised by a great deal of product differentiation and yield management. Airbnb has reciprocity at play, as guests and hosts switch roles. Additionally, hotels and airbnb hosts have different cost structures and different business models.
Furthermore, consumers have different amounts of information: bounded rationality and satisficing are at work. So even if the offers were identical (they're not), and people's preferences were identical (they're not), then people would still make different decisions.
product differentation
Although you always prefer a lower-cost hotel-room to airbnb, some other people will prefer airbnb, even when presented with identical information. That's because they are not identical offers: they have many  different characteristics (flexibility, physical space, presence of host, services offered, location, the P2P feelgood effect, doing business with individuals rather than faceless chains, staying in someone's unique home rather than just another clone room that looks almost identical in most of the world). And different people weight those characteristics differently: no two consumers have identical preferences.
yield management
Different people will also be booking at different times, with varying flexibility. Hotel rooms, (like airline seats), are one of the paragons of yield management, used in many textbooks' explanations of it.
reciprocity
Because with airbnb hosts can become guests, and guests can become hosts; and because reputation plays a major role in the market, there is reciprocity at play: both sides are incentivised to deal fairly with each other, rather than the practice of many hotels of making repeated attempts at getting more and more money from the customer from additional goods and services sold in addition to the basic accommodation, sometimes by using deception in the initial offer.
cost structures
On the supply side, airbnb and hotel rooms have different cost structures: an hotel room that's empty for the night is a wasted asset, and there may be little opportunity to reduce associated costs. Whereas a home without an airbnb guest is still a home, the residents get to have it all to themselves, and don't have to do any additional hosting, laundry, cleaning or tidying.
business models
A hotel's entire income is dependent on it renting its rooms out and selling associated services. For an airbnb host, the airbnb income is usually an additional source of income, a bonus rather than the thing that keeps a roof over the head and puts food on the table. So there is not an urgent and immediate need to find a guest, allowing them to set higher prices and tolerate a lower take-up.


Does merger control really affect market structure? Pretty much since 1976 (the passage of Hart-Scott-Rodino Act) US antitrust authorities have been reviewing mergers, challenging only 1.8 per cent of the total number of above-threshold notifications (IIRC I read it in a book by Bob Pitofsky).

What are the studies that control for changes in technology, capital availability and perhaps other factors and quantify the impact of merger control on economy-wide market structure/concentration measures?

Clifford Winston´s excellent book Government Failure versus Market Failure:
Microeconomics Policy Research and Government Performance surveys the literature on the effects of government regulation generally and antitrust merger control specifically. He doesn't exactly answer your question on economy-wide structural effects, but largely concludes that merger control is rather ineffective. A small quote:

  Evidence from the finance literature indicates that mergers that were
  challenged by the DOJ and the FTC were in general not anticompetitive
  and would have been efficient had they been allowed to go through
  (Eckbo 1992). Mergers that were challenged or opposed by antitrust
  regulators but were consummated anyway have often resulted in gains
  for consumers (Schuman, Reitzes, and Rogers 1997; Morrison 1996).
  Finally, Crandall and Winston (2003) analyzed the effects of merger
  policy on price-cost margins and found that the antitrust authorities
  have primarily attacked mergers that would enhance efficiency, either
  by blocking them in court or allowing them to proceed only if the
  merger partners agreed to conditions that turned out to raise their
  costs.


locally nonsatiated preferences what does this symbol mean in the discuss of locally nonsatiated preferences:
$\varepsilon > 0$ and $||y-x||<\varepsilon$.

If you take the vector $\mathbf{x}$ as the center and an $\epsilon > 0$ sufficiently small as the radius, then the open ball (local neighborhood of the vector $\mathbf{x}$) is the set of all vectors $\mathbf{y} \in \mathbb{R}^{n}$ whose distance to the center $\mathbf{x}$ is less than $\epsilon$ measured w.r.t. the metric $\Arrowvert \cdot \Arrowvert $, i.e., more formally as

$$\mathbf{B}(\mathbf{x},\epsilon) := \big\{\mathbf{y} \in \mathbb{R}^{n}\,\Big\arrowvert\, \Arrowvert \mathbf{y} - \mathbf{x} \Arrowvert < \epsilon \big\}.$$

Notice that measuring a distance by a metric is only possible within a metric space or normed space like Hausdorff or Banach. Topological spaces do not have in general a metric, in this case the above concept must be generalized. Fortunately, all finite dimensional spaces have a canonical norm, i.e., the Euclidean norm.


CES production function with non constant returns to scale In the equation
\begin{equation}
Y=\left[ aK^{\frac{\sigma -1}{\sigma }}+\left( 1-a\right) L^{\frac{\sigma -1%
}{\sigma }}\right] ^{\frac{\mu \sigma }{\sigma -1}}  \label{ces_pf}
\end{equation}
if $\mu \ne 1$ we have non constant returns to scale (RTS).
This is the only way I can see to get non constant RTS into a CES production function. One cannot have factors which are raised to exponents which sum to above or below one since that violates the form of the CES function.
Is there some other way to get non unitary RTS into the CES function?

Another possibility is
\begin{equation}
Y=\left[ aK^{\mu_K\frac{\sigma -1}{\sigma }}+\left( 1-a\right) L^{\mu_L \frac{\sigma -1%
}{\sigma }}\right] ^{\frac{ \sigma }{\sigma -1}},
\end{equation}
with $\mu_K+\mu_L \neq 1$.
Edit: The function is not homothetic in $(K,L)$, and as mentioned by Giskard, the elasticity of substitution is not longer constant, unless $\mu_K=\mu_L$, in which case we obtain the specification proposed by cel.


How to obtain real money balances data Theoretically real money balances ($m_t$) are defined as:
$m_t=\frac{M_t}{P_t}$
Where $M_t$ are nominal money balances, and $P_t$ is the price index of the economy. If I were to make an empirical study involving real money balances, what is the correct approximation for obtaining time series of this variable?
My try is obtaining time series for M1, that would be my empirical nominal money balances, as well as obtaining some price index time series as CPI. Then my real money balances time series would be the result of computing in each cross-section:
$\text{real money balances}_t=\frac{M1_t}{CPI_t}$
Is that right?

There is no real good general answer for that without detailed knowledge of model you want to estimate. When it comes to $P_t$ people typically use $CPI_t$ as a proxy but when it comes to $M$ it depends on what sort of work you are doing. Some work in fact even estimates $M/P$ in different versions using $M_1$, $M_2$ and $M_3$ (such as Short 1979).
In typical macroeconomic model $M$ is interpreted more broadly than just base money (e.g. see discussions in Woodford Interest & Prices, or across Romer Advanced Macroeconomics). In that case using $M_2/CPI$ or even $M_3/CPI$ would make more sense if you would be forced to choose only one. But as in the above mentioned citation you can construct it in various different ways and then see if the results are robust when you switch the measurement.


Conceptual explanation/prediction of utility function. Extraction of utility function from Big Data It seems to me, that utility function usually is just a set of facts. Is there a framework or model for utility function that can explain or predict utility function. I. e. if user has value for item A and B and there is item C (which is conceptually linked to items A and B, i.e. it has the color or A and usability features of B) then this framework can predict the user's value for item C?

Maybe there ir some kind of framework that can explain utility function? I.e. there are ontologies which have ABox component which is set of concepts and TBox component which set of instances of those concepts. Maybe there is framework that can list concepts that are linked to some products and each consumer have some value on those concepts and from this it is possible to derive the utility function for the actual products?

How utility function is used for modeling single customer profiles? Maybe utility function can be extracted from the Big Data that are associated with cash register data, contact calls and so on?

Is there some trend of research and practice along these lines? Maybe these are fairly common things and I don't know relevant keywords only?

I believe what you are looking for are hedonic regressions:

  In economics, hedonic regression or hedonic demand theory is a
  revealed preference method of estimating demand or value. It
  decomposes the item being researched into its constituent
  characteristics, and obtains estimates of the contributory value of
  each characteristic. This requires that the composite good being
  valued can be reduced to its constituent parts and that the market
  values those constituent parts. Hedonic models are most commonly
  estimated using regression analysis, although more generalized models,
  such as sales adjustment grids, are special cases of hedonic models.

  An attribute vector, which may be a dummy or panel variable, is
  assigned to each characteristic or group of characteristics. Hedonic
  models can accommodate non-linearity, variable interaction, or other
  complex valuation situations.

  Hedonic models are commonly used in real estate appraisal, real estate
  economics, and Consumer Price Index (CPI) calculations. In CPI
  calculations hedonic regression is used to control the effect of
  changes in product quality. Price changes that are due to substitution
  effects are subject to hedonic quality adjustments.

Hedonic regression on Wikipedia

The BLS has a nice fully worked example about using this method to price changes in the quality of camcorders. They explore how brand, storage format, image stabilization, weight, and other features influence the price in order to capture how changes in the value of camcorders influences substitution in consumption decisions.


What effect does a wage ratio cap have on the efficency of allocation of labour? Introduction

Wage ratio caps prevent the wages of all employees from exceeding a maximum of a fixed multiple of the wages of the lowest paid employee in a given institution.

Wage ratio caps can apply to both the public and private sector. In some places they have been introduced as company policy. Though they are yet to have been implemented, they have also been proposed as legislation in some countries.

Question

What effect does a wage ratio cap have on the efficency of allocation of labour?

I'm having difficulty with comparing this to other policies which directly represent price ceilings.

I see one main difference with pay ratios: companies can always compete to provide high pay for their executives. A company can always offer a more competitive wage for its executives by paying its lowest earning workers more. This is different to price controls like a rent control, where a landlord does not have access to a lever which raises the rent they can charge.

I would accept an answer that can show that the policy has the same effects as a price ceiling, but I'd also like to see explanation of the consequences for the labour market.

The effects can be quite different from a price (wage) ceiling. The baseline case where you have homogeneous, inelastically supplied labor that's free to move across different "types" of work produces no supply response in reaction to a wage ceiling, but leads to complete specialization in one type of labor or another in the case of enforced bounds on relative wages which rule out the competitive market allocation.

For companies, enforcing internal wage ceilings may be a way of trying to address problems of corporate governance - the shareholders may be trying to address a principal-agent problem by getting such a policy instituted within the company. In that case, it may well improve efficiency, but it's hard to say if there would be a significant impact on the supply of executives available for corporate management.


Open offer made by companies to take over What is open offer in simple terms? What is its meaning in cases of taking over the major stakes in other company?

An "Open Offer" is not necessarily the same as a "corporate takeover."

An "open offer" (as defined by the link above) is

  the opportunity to purchase stock at a price that is lower than the current market price

An "open offer" is primarily used to raise funds for the company.

However, it is also important to note that, in an "open offer,"

  a company allows existing shareholders to purchase additional shares directly from the company in proportion to what they currently own. This is to prevent dilution to existing shareholders

Since the existing shareholders own the same proportion of stocks both before and and after the "open offer," the leadership of the company does not necessarily change.


How does reverse repo rate affect money supply? What is the impact of increase/ decrease of reverse repo rate on Monetary Base, Money multiplier and therefore, overall money supply?

Reverse Repo Rate (RRR) is the rate at which the central bank "borrows" money from commercial banks. (In practical terms it refers to the surplus funds that these commercial banks park with the central bank.)

This leads to a FALL in the total money supply as it soaks liquidity from the market.

This reduction in total cash flow in economy (which is now lying stagnant at the central bank) implies a weakened monetary base and reduced capability of banks to "create" more money as they are left with little real cash to extend loans upon given the cash reserve ratio requirements.


Homothetic preferences and weak separability With 3 goods (x,y,z), linear Engel curves, where z is separable of x and y, and with all first derivatives are positives and second negatives.

Does the demand of z change with the price of x or y? So, is z independent of $p_{x}$ and $p_y$?

I think so, because I have made some examples where changing prices didn't change the optimal amount of z. However I cannot find a formal proof.

EDIT: Seems to that after your most recent edit the answer is still no.
A relatively simple counterexample is:
$$
U(x,y,z) = \sqrt{x} + \sqrt{y} + \sqrt{z}.
$$
This is clearly seperable and homothetic. But $D_z$ is is not independent of $p_x$ and $p_y$. I think this is clear just by looking at the utility function, as it is not of the Cobb-Douglas type. If you have doubts you can calculate $D_z$ from these equations:
\begin{eqnarray*}
MRS_{xz}(x,y,z) & = & \sqrt{\frac{z}{x}} = \frac{p_x}{p_z} \\
\\
MRS_{yz}(x,y,z) & = & \sqrt{\frac{z}{y}} = \frac{p_y}{p_z} \\
\\
m & = & p_x \cdot x + p_y \cdot y + p_z \cdot z.
\end{eqnarray*}
Then
\begin{eqnarray*}
m & = & p_x \cdot x + p_y \cdot y + p_z \cdot z \\
\\
m & = & p_x \cdot z \cdot \left(\frac{p_z}{p_x}\right)^2 + p_y \cdot z \cdot \left(\frac{p_z}{p_y}\right)^2 + p_z \cdot z \\
\\
\frac{m}{p_z}\frac{1}{\frac{p_z}{p_x} + \frac{p_z}{p_y} + \frac{p_z}{p_z}} & = & z.
\end{eqnarray*}
As you can see both $p_x$ and $p_y$ appear.


Maximum level of profit attainable when discount factor is too low This is a question I encountered during my undergraduate studies in Industrial Economics. So the question goes like this:

  Consider two identical firms with constant marginal cost $c$ which
  compete in quantities in each of an infinite number of periods. The
  quantities chosen are observed by both firms before the next play
  begins. Inverse demand is given by $p = 1 – q_{1} – q_{2}$. The firms use
  ‘trigger strategies’ and they revert to static Cournot behaviour if
  cooperation breaks down.

  What is the lowest value of the discount factor $\delta$ such that the
  firms can sustain the monopoly output level?

This part I can answer and the value of $\delta$ needed to sustain the monopoly output level turns out to be $\frac{9}{17}$.

Now onto the second part of the question:

  Suppose $\delta$ is too small to sustain the monopoly output. In
  particular, suppose $\delta = \frac{1}{2}$. What is the most profitable subgameperfect
  equilibrium that can be sustained using trigger strategies?
  (Assume $c = 0$ for simplicity.)

So my line of thinking for this is, to sustain collusion the profit from colluding has to exceed the profit from defecting one period plus the punishment profit in subsequent periods.

$$
\pi^{C}\frac{1}{(1-\delta)} \geq \pi^{D} + \pi^{P}\frac{\delta}{(1-\delta)} \tag{1}
$$

Having from secion 1 of the question:

$$
\pi^{C} = \frac{(1-c)^2}{8},\quad \pi^{D} = \frac{9(1-c)^2}{64},\quad \pi^{P} = \frac{(1-c)^2}{9} \tag{2}
$$
Take into account that $\pi^{C}$ is the profit each firm obtains if they collude, i.e. monopoly profit divided by 2.

So, to me section 2 of the question is asking about $\pi^{C}$ (in condition $(1)$) when $\delta=\frac{1}{2}$. I know $\pi^P$ remains the same since it is the Cournot profit but I guess $\pi^D$ changes because it was calculated assuming the other firm would produce the monopoly level of output and this is not the case anymore since $\delta$ is lower than what is needed to maintain that level of output.

You can see I am a bit confused. Can anyone help me?

I do not want to do all the algebra, but I give you a hint.
You are correct: You are asked about $\pi^C$ in your Condition (1) and you are also right that $\pi^D$ changes.

In your parameter setting with $c=0$:
$$\pi^C := \pi (q^C, q^C) = (1- 2 q^C) q^C,$$
where $q^C$ is the quantity they coordinate on.

Then $\pi^D$ is the profit from best-responding to $q^C$ with some $q^D$:
$$ \pi^D := \pi (q^D, q^C) = (1- q^C-q^D)q^D,$$
i.e., $q^D = \arg max \quad \pi^D$. Now you solve $q^D$ as a function of $q^C$ and plug that into $\pi^D$. Having Condition (1) hold with equality gives you some $q^C$ that you can plug into $\pi^C$ again.


own and cross elasticity for many products This publication uses this formula to fit a model to predict the demand of a product A:

Log_Demand_A = constant + b1*log_Price_A + b2*log_Price_B + b3*Promo_1 + b4*Promo_2 + b5*log_Price_A*Promo_1 + b6*log_Price_A*Promo_2

I have 2 questions.

What is done in practise when businesses sell hundreds of products? Could one fit several models for product A (e.g. own for own elasticity and let's say we have 2 other products B and C, another one for the interaction A->B and another one for the interaction A->C and the combine the demand prediction using some kensemble method).
Are the 2 promos in the above formula specific to product A (i.e. do not necesaarily apply to product B)?

this comes from a standard cob-douglas utilty function such as $U=A^\alpha\cdot B^\beta$ w.r.t a budget constraint. If you take a monotonically increasing function of U such as a log which leads to $ \ln (U) = \ln (A^\alpha\cdot B^\beta) -> \alpha \cdot \ln (A) + \beta \cdot \ln (B)$ by solving this via a method like subbing in the budget constraint to get the indirect utility form and adding some dummy and interactions to control for the promotions you get the form above. You can see that this is founded purely from first principals but runs into the "too many parameters" problem when you have many products as you correctly anticipated. Imagine we have 100 products and we need to calculate the elasticity for every product pair. Well then we would have 100 equations with 100 elasticity parameters + 100 intercepts and whatever promotional dummies = $ 100 \cdot 100 + 100 10,100$ minimum parameters. As you might not even have this many data points and not enough to measure efficiently you run into problems and need to use other methods that impose more assumptions on the data.


Finding Pareto efficiency with negative externalities Student S has one hobby of listening to music. The noise of the speaker can produce noise up to 100 decibels (measured by D). Her money is measured by Ms . Her utility function is Us = 10D1/2 + Ms
Student F has a utility function of UF = 10(100-D)1/2 + MF . MF is Student F’s money and D is the decibels of Student S’s speaker.
What is a Pareto-Efficient Level? (We also learnt in the previous part that Student S has no money, we do not know about Student F)
I am aware that Pareto-Efficiency means we can’t make one student better off without making another student worse off, but since one likes loud music and one does not like any music. Isn’t any level of noise Pareto-Efficient?

Your statement "Isn’t any level of noise Pareto-Efficient?" would be true only if the only good traded was "levels of noise". Indeed, given a single good, Pareto-Efficient means that you simply do not waste anything.

I understand that here you have two exchangeable goods, Decibels and Money, and you need to evaluate possible combinations of the two. You'll see that, your task is to find the combinations of decibels and money, which is done by finding the contract curve.

The common method, as I'm sure you have learnt, is the comparison of the two persons' Marginal Rates of Substitution, in your example: $ MRS_F = MRS_S$, as given by the Edgeworth Box:
Notice how all Pareto-Efficient contracts lie in the contract curve? You can use this equation to input values for decibels and get the requested "Pareto-Efficient" level. The hint on the budgets of the two students also works in favor of you finding a proper budget constraint and finding precise levels for the two commodities.
This would be my process.


Who gets newly printed currency? The central bank of a country is responsible of the printing of new currency notes and coins/ money to the economy of a country. My question is how they introduce this new money into the economy in a 'fair' manner. Giving it to one individual or group would be privileging them against other such groups, right? So, how is it done?

One way to think about this is that money is put in circulation when the central bank buys assets from the citizens of a country. Sometimes this is really the main thing going on, for example, to perform QE the Fed bought all kinds of securities from financial markets. When the fed buys these securities it pays banks by increasing the deposit balances of those agents selling the asset.

Another simple way that a central bank "buys assets" is when it gives a loan to a commercial bank. In the process of given the loan, the central bank will give physical cash to the commercial bank and keep the loan in its books as an asset.

This could also happen in an accounting sense but not in an economically meaningful sense, for example when a central bank "buys" bonds issued by the government of its country. The government might never pay or the bonds might loose most of their value if inflation increases interest rates for example, so its a kind of fake purchase.

Finally, economists talk about a 'helicopter drop', where the central bank would print money and then just through it out fro a helicopter, hoping it is evenly distributed among the population... but that's mostly just an imaginary scenario.

[BUT, NOTE: This is a caricature of how physical currency can be printed by a bank and shipped out. Quantitatively, an important part of money creating takes place within the banking system, as banks receive deposits from clients and give out loans, physical money gets "multiplied".]


Unit root testing in Eviews I've plotted my data log(GDP) which displays an albeit small upward trend.

However, after performing an ADF unit root test log(GDP) it suggests that I can reject H0 [that there is a unit root] at the 5% level. I tested the level effect with trend and intercept due to the nature of the graph. Both the intercept and trend are statistically significant and removing the trend only makes the t statistic lower so that you can reject H0 at the 1% level.

Why might I be getting this result as from the graph the data definitely looks nonstationary.

I think the source of your confusion may be due to the inclusion of the linear trend term in your test. If you exclude the linear trend from the test then you will almost certainly find evidence of a unit root. There is actually an open debate as to whether GDP is trend stationary (i.e. stationary once you remove the linear trend) or difference stationary (i.e. stationary once you take a difference of the series). For example, see: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=866624

To help you better understand it is possible to illustrate this with a simple model with a lag and a trend (this also generalizes for two lags but it is good to keep things simple). Consider the following model of GDP:

$y_{t}=\alpha+\beta y_{t-1}+\gamma t+e_{t}$

If we subtract $y_{t-1}$ from both sides we get that

$\Delta y_{t}=\alpha+(\beta-1) y_{t-1}+\gamma t+e_{t}$

where the null hypothesis of our unit root test is that $(1-\beta)=0$. The test depends on whether we account for the constant ($\alpha$) and the linear trend ($\gamma$) or not. If the true process has a linear trend but $\beta<1$ then you will not detect a unit root when including a linear trend in the test. On the other hand if you estimate the model without a linear trend and conduct the unit root test without an exogenous linear trend then the unit root test should not reject the null since the estimate for $\beta$ will move towards 1 to try and capture the linear trend. For this same reason if you have large structural breaks in the data the estimate of $\beta$ will move towards 1 and suggest evidence of a unit root (regardless of an inclusion or a linear trend or not).

Long story short if you include the linear trend in the test even if you exclude it from the estimated regression model then you are unlikely to find evidence of a unit root in an empirical process where a linear trend dominates unless the data were even more non-stationary than it appears.


Why do low labour and wage flexibility forestall a single currency? The European Union: Politics and Policies (2017 6 edn). p. 77 Middle.

Please see the red line beneath. Doesn't low labour and wage flexibility befit a single currency? If labour and wage fluctuate, then a single currency would become unstable?

It's probably referring to the standard OCA theory of the tradeoff between symmetry and flexibility, but in the latter flexibility is usually one index:

The theory of optimal currency areas (OCA) has created a set of ideas that has an significant influence on the governance of the eurozone and on views about how this governance should be strengthened in the future. The best way to make this clear is to present the core of the OCA theory, using a well-known graphical representation of this theory (see De Grauwe (2014)). This is done in Figure 3. On the horizontal axis we set out the degree of flexibility in the labour and goods markets.
This measures the degree to which wages and prices adjust freely to shocks and the degree to which workers are mobile. We assume that these different dimensions of flexibility can be represented by one index. On the vertical axis we set out the degree of symmetry between countries, i.e. the degree of co-movement (correlation) of macroeconomic variables such as output and employment. Thus, when there are a lot of asymmetric shocks we move downwards along the vertical axis. By contrast, when shocks become less asymmetric we move upwards along the vertical axis.
The downward sloping OCA line represents the trade-off between symmetry and flexibility. Hence, when the degree of symmetry declines (there are more asymmetric shocks) countries in a monetary union need more flexibility to deal with these shocks.

The OCA-line separates the space into two zones. The OCA-zone above the OCA-line contains the collection of points at which symmetry and flexibility are high enough to guarantee that the benefits of the monetary union exceed the costs. The points below the OCA-line are the points at which symmetry and flexibility are too low, i.e. countries located in that zone will find that the costs of the monetary union exceed the benefits. The OCA-line that separates the two zones can therefore also be defined as the collection of points for which the benefits and the costs of the monetary union are equal.

So they probably mixed up usage a little and instead of wage flexibility and labor mobility they referred to labor flexibility in the 2nd term. I suppose the latter may encompass the former for some broad meaning... but then it also includes wage flexibility.
And if the quoted theory above isn't too accessible, a simple illustration is to consider Greece: its economy was quite unlike Germany's. So in order to respond to the (asymmetric) shock the Eurozone experienced as a whole via the Greek problem, Greek workers had to take lower pay or migrate to other EU countries. And they did both to some extent. Of course, the flexibility question/measure is how fast these two reactions happen in response to a shock.
Finally, labor mobility works better as an automatic stabilizer if you also have  federal taxes; without these you need some other mechanism to transfer money from the income of the workers that have migrated back to the problem area of their origin.