Should one remove trend from time series before testing for cointegration? Should one remove trend from time-series before testing for cointegration? I guess no, but I couldn't find any answers yet.
Also is it necessary to remove trend before estimating a VAR model if the trend is the same across the variables like in the plot below?

It is not necessary to detrend the series although the trend has to be dealt with and detrending is one of the options but there are also other options.
Other options include explicitly modeling the trend. For example, many tests for cointegration including Johansen cointegration test, it is possible to estimate the test together with a linear or quadratic or other deterministic trend terms. The only issue there is that with some cointegration tests the test statistics with and without trend and critical values are different, but most modern packages/programs already provide adjustments for some common deterministic trends - for example linear or quadratic trends.  Hence in such cases this might be preferable to detrending.
However, detrending the series is still an option. The problem with detrending is that you are modifying the series itself and there is always a risk that when you remove trend you are also throwing away some other information that the series had. Nonetheless, it is still a valid option.


What is the correct way of calculating the "average" price based on the "Open,High,Low,Close" daily trade fields? Open,High,Low,Close

I have these fields, representing the "opening" amount, the highest for the day, the lowest for the day, and what it closed at.
I'm trying to determine the "average" price for the day.
I currently do this:
(Open + High + Low + Close) / 4

Is this correct? I get slightly different numbers if I do:
(High + Low) / 2

Which one is correct? Or, most common/used?

You cannot obtain that information with the data provided.
You would need periodic samples throughout the day.


Why does a buyer value a dollar in a small purchase (e.g. TV) differently to a dollar in a large purchase (e.g. car)? I am referring to how buyers will haggle over 200 when purchasing an item worth, say, 500 but not bat an eyelid paying an extra 5000 on, say, a house.

I am seeking a very brief explanation of this phenomenon or the official name (if it has one).

One explanation from psychology and behavioral economics is "mental accounting": people put different transactions into different mental accounts.

When buying a house, people are imaging (probably unconsciously) a bank account dedicated to that purpose. The account's balance is pretty large (including mortgage loans). \$5000 in or out of this account does not really have any significant impact on the account.

When buying a cellphone, people are imaging a separate bank account, of which the size is much smaller than the home purchasing account. \$500 in or out of this mental account makes a big difference.

If we pool all accounts together, then \$500 saved from buying a cellphone should be the same as the \$500 saved from buying a house.


EU and North America with CETA The CETA trade deal is supposed to involve only the EU and Canada, but Canada has already a trade deal with the USA and Mexico : I don't understand how this is possible.
For example, if I own one company in Paris, one company in Toronto and one company in New York, I can sell my product to myself from Europe to Canada and then from Canada to the US (or all in reverse). How could any tariff apply in such a case ? (my product never crossed a "trade border", yet it moved freely from EU to USA )

"Rules of origin" cover this. Try

Wikipedia https://en.wikipedia.org/wiki/Rules_of_origin or
WTO: https://www.wto.org/English/tratop_e/roi_e/roi_info_e.htm  or
EU: https://ec.europa.eu/taxation_customs/business/calculation-customs-duties/rules-origin_en or
USA: http://2016.export.gov/FTA/nafta/eg_main_017791.asp

Essentially the rules tell someone trading between two places with a free trade agreement in which circumstances something partly originally imported from a third country (whether under another free trade agreement or having paid an original tariff) can be freely traded under the agreement


In 21st century and a globalized world, is economic growth still the metric by which to measure a state's success? Economic growth as a yardstick for a government's success is relatively new on a human historical scale. In my thinking it has arisen out of an expansion of the expected function of a state. States at a minimum are expected to uphold the rule of law and protect its people and its interests. Economic growth arose out of the need to implement not just criminal justice but also social justice. Now with globalisation and the breakneck speed with which developing countries are growing economically, economic growth is so deeply entrenched. However, it is possibly unsustainable and as things stand culturally and environmentally harmful.

Are there ways to either
- eschew growth in favour of something better

constrain and direct growth in a way that is culturally and environmentally sensitive?

Depends on what you mean by "success".

Economic growth is simply change in gross output expressed in market prices. Prices tell you what citizens want and how much of it they have. Equating marginal utility with price is a useful abstraction in this case.

Economic growth is trivially desirable: it's about people making things they need.

When "success" is defined in some progressive terms, it's no longer trivially desirable. Zero employment policies — like those in the Soviet Union — hurt productivity. Premature investments in clean tech worsen intertemporal tradeoffs. You actually get back to GDP to measure these successes.

Still, measurements of economic growth can get better. Like Stiglitz et al's suggestion to use net disposable income instead of GDP per capita (see Commission on the Measurement of Economic Performance and Social Progress, Mismeasuring Our Lives). Adjusting per-capita metrics for inequality would also be a good idea.


How was the year 1925 chosen as a dividing point in the history of economic thought? The JEL codes divide "History of Economic Thought" into "through 1925" and "since 1925".
What is the significance of the year 1925 in the history of economic thought? Or was this just some cutoff point that was quite arbitrarily chosen?

tl;dr:
It is most likely an arbitrary date because they had to set some year. In fact the year 1925 is not even a strict guideline but only loose criterion. As such the year was not set due to some special significance.
The JEL classification also responds not just to the needs of academicians but also grant agencies, government, university HR departments etc. and so classifications might be arbitrarily set in ways that do not necessary always correspond to what economists believe. However, there are some subtle hints it could have something to do with the advent of Neoclassical Economics.
Full Answer:
The JEL codes are set by American Economic Association (AEA) as they were originally developed for their Journal of Economic Literature. As such AEA is really the only authoritative source on this issue.
Normally classification codes come with guidelines but in this case JEL guidelines for "History of Economic Thought through 1925" just read:

B1 History of Economic Thought through 1925:
Guideline: Not Specified.
Keywords: Economic Thought.

However, B1 is just general category that is further subdivided into smaller sub-categories B10-B19. When you look at each of the B10-B19 guidelines individually most of them include the following caveat:

Caveats: The demarcation year of 1925 is used as a loose criterion.

When we look at the classification guidelines for History of Economic Thought since 1925" we find the following guidelines:

B2 History of Economic Thought since 1925:
Guideline: Studies that are also relevant to contemporary economics or
economies should be cross-classified here and under the other
appropriate categories.
Keywords: Economic Thought, Neo Classical.

Again quite vague but the keyword 'Neo Classical', is suggestive and suspiciously inserted there especially since neoclassical economics (although technically possible to trace prior to 1900s) first gained on prominence in early 1900s (see the History of Economic Thought by Brue and Grant). Although this is really not enough to be certain.
Also as in the previous case B2 is split into multiple sub-categories ranging from B20-B29 and most of them again include the following caveat:

Caveats: The demarcation year of 1925 is used as a loose criterion.

Furthermore, there is actually paper published by JEL about history of it's classification system and how it developed to it's present form. According to Classifying Economics: A History of the JEL Codes by Beatrice Cherrier (2017):

... Yet the AEA classification
does not provide a pure image of the discipline. Instead, it is a compromise between
looking forward and looking backward,
between AEA officials’ sometimes conflicting visions of their science and the multiple
and contradictory demands they face: editors
needed a way to select reviewers and referees; recruitment committees needed a way
to classify job candidates and their output;
the government wanted a system to draft
economists into the war effort, and later to
recruit specialists into the various bureaus
concerned with monitoring and managing
economic affairs; librarians needed help in
indexing papers and books; and the National
Science Foundation (NSF) needed a classification to quantify and evaluate national
scientific expertise ...

Author further states:

JEL codes reflected changes in
the ways theory and applied work interacted.
Second, the codes point to the transformation of the subject matters of the discipline
and the rise and fall of different approaches
to economics. Third, they reflect changes in
the external pressures on the discipline and
information technology

Furthermore, as the article explains the classification codes undergo 4 revisions and were originally set up 1911. Consequently, the year 1925 was not originally even part of classification and might very well change in the future.
The article also tells a fascinating story of how these classifications came to be and most of them were results of compromise between various stakeholders and economists holding different opinions on how to classify economics thinking. It is a result of a messy process rather than some unanimous academic consensus.
Lastly, I actually written an email to AEA requesting clarification. They confirmed that the year 1925 is not strict criterion and the person I corresponded with simply stated they do not know how the criterion was set. I am not publishing the e-mail as I don't know what would legal ramifications of such act be, and my e-mail address contains my real name, but I expect that anyone making the same inquiry would receive the same answer.
So what can we conclude from the above?

I think the evidence above points clearly to the fact that 1925 is just a loose guideline. The year itself has no special significance.
The keyword Neo Classical for B2 category is suggestive that development of Neoclassical economics could have something to do with it as it occurred around the period set by the 'loose criterion'.
The classification has to be set not only for needs of economists but also bureaucratic needs more widely and as such it might not always reflect purely academic opinions.
AEA employees (or at least one of them) themselves do not know why 1925 was chosen. Given that the most recent revision of JEL codes is over three decades old it is possible that such knowledge is lost to us.


Is the utility of money *actually* logarithmic? Apologies for asking what is probably a basic question from someone that is not in the economics field.

But I was playing around with the idea of determining how a group of people could split a bill "fairly", meaning they each spend an equal amount of utility, calculated from their yearly income. And I did it using logarithms since that is the common recommendation.

I have seen many mentions that the utility of money is roughly logarithmic as it increases. And it is usually phrased as a rule of thumb, but I don't see actual justification. And the assumption seems embedded everywhere. For instance, a (real) flat income tax that taxes all income (not just consumption or earned income) is seen as neither regressive nor progressive - but the flat tax assumption (that everyone would pay the same percentage) again points to the idea of money having logarithmic utility.

My question is, has this actually been measured? I have seen indications that economists actually do studies where they analyze purchasing decisions across a wide range of income levels. It seems that with enough data points, a utility function could actually be calculated.

Has this been done? And is it actually logarithmic? What is it? Is there an up to date utility function for the value of money?

"Essentially, all models are wrong, but some are useful"
George Box,  Empirical Model-Building and Response Surfaces

To what approximation would one like to know the utility of wealth?

To be guaranteed that a utility function representation of preferences exists you need a number of assumptions about preferences to hold. Usually, these are Completeness and Transitivity with Continuity, Monotonicity, and Convexity common additional assumptions to give the nicely behaved preferences we see in most economics settings. Levin  and Milgrom (2004) provides a technical, but short overview of the definitions and derivations in this branch of economics called "Choice Theory".

But that's just for ordinal utility functions (functions which rank bundles of goods but resulting the utils have no economic meaning beyond that a bundle with higher utils is preferred to one with lower utils) to exist. It turns out that the preferences of ordinal utility functions are preserved by any positive affine transformation. To get a particular functional form like $log(x)$ to matter you need cardinal utility where the values of the preferences matter (although even here they can be re-scaled by a positive constant and a constant added). Cardinal utility functions are more common in finance and macroeconomic settings even though more is required for such a utility function to exist. As Wikipedia says:

  The idea of cardinal utility is considered outdated except for
  specific contexts such as decision making under risk, utilitarian
  welfare evaluations, and discounted utilities for intertemporal
  evaluations where it is still applied. Elsewhere, such as in
  general consumer theory, ordinal utility with its weaker assumptions
  is preferred because results that are just as strong can be derived.

Cardinal utility

Given the findings of behavioral economics experiments, which provide evidence that preferences may violate completeness and transitive axioms, it is likely that no such "true" function exists. However, as Box's quote indicates, they may still be useful.

The log utility function has nice properties. The logarithmic utility function is a special case of constant relative risk aversion (CRRA) utility function. Roughly speaking, this family of utility functions views risks in percents of wealth as constant for all levels of wealth. That is, rich and poor alike worry the same about a 10% shock to wealth. Equivalently, the utility "pain" of spending 10% of wealth on something are the same at all wealth levels. This is an example of a function with a declining marginal utility of consumption.

Log utility is particularly easy to work with because it has simple derivatives and reflects a "low" but non-zero level of preferences over risk. Also, under log utility the wealth and substitution effects of interest rates cancel out in intertemporal choice problems, which further simplifies some models. In portfolio allocation, log utility maximization is effectively maximizing the geometric mean return the return in the long run, which feels intuitively sensible as an investment goal for the long run investor. Also, when working with shocks to wealth that are log-normal and a log utility function, there are nice closed form solutions to the values of expected  utility (they are slightly more complex in the CRRA case). Here is an example of trying to calibrate CRRA utility using experimental data:

  For this specification of CRRA, a value of 0 denotes risk neutrality,
  negative values indicate risk-loving, and positive values indicate
  risk aversion.  Thus we see clear evidence of risk aversion: the mean
  CRRA coefficient is 0.64. This distribution is consistent with
  comparable estimates obtained in the United States, using college
  students and an MPL design, by Holt and Laury [2002] and Harrison,
  Johnson, McInnes and Rutström [2003a][2003b].

Harrison, Lau, Rutstrom (2007)

If CRRA were the proper specification and the experimental point estimates recovered the true CRRA parameter, then we would be close to log utility which occurs when you take the limit of a CRRA utility function as the coefficient approaches $1$.

In conclusion, there is some empirical evidence that preferences can be approximated with a log utility function and it is very easy to work with.


Equilibrium with Externalities: Solving without FOC I have a general equilibrium problem, where households given objective function $U(c,n)$ solve for working hours and consumption $n, c$, and firms use labor to produce a consumption good - their objective function is $V(n)$. There are potentially profits, which is paid out to the workers through wages $w$. Households spend all their labor income on the production good.

There is the externality that working more leads to higher income on the household side, and spending higher income onto the consumption good yields higher profits for the firm - in turn leads to higher wages for the household. These things just happen in my environment, take my word for it - I'm trying to simplify as much as possible.

Usual Equilibrium Household optimality, firm-side optimality and market clearing means that all FOC have to hold. Usually, I would solve this taking the first-order conditions for $U(c,n)$, taking firm's demand $Y$ as exogenous, and replace - after taking the FOC - $Y = nw$.

Here, instead I want to rather find my equilibrium without FOC. It is $w, n, c$ such that

Firms behave optimally: $V(n) \geq V(n')$ for all $n'$
Households behave optimally: $U(c,n) \geq U(c',n')$ for all $c', n'$
$wn = Y$

This makes much more sense for me since it is in this environment much easier to find the stationary state in the objective functions rather than the roots of the first-order conditions.

However, I'm worried that without two steps, I cannot "first solve FOC, then replace $Y=wn$. How do I ensure that household's are neglecting the externality of their labor/consumption choice?

It is my impression that there is an inconsistency here.

If firms want to maximize $V(n)$ which is some "surplus revenue over costs" function, then surplus they will produce. Meaning, that this surplus/profits cannot be given to workers, in the form of wages, because wages are cost. It may be given as dividends or, say, end-year bonus, but in any case it won't be related to $n$.
So we do not have $Y=wn$ but rather $Y = wn + d$, and the externality appears to break down.

The $Y=wn$ relation is consistent with a "non-profit" organization, which would demand as much $n$ as needed in order to have zero profits. In such a case, the wage would be equal to the average product of labor, not the marginal one.


Why does the US government not invest in the stock market? We often talk about the huge public debt of the US government. Why does it not invest in the stock market (at least in index funds) instead of issuing debt? Can they not reduce the debt that way?

The US government could do that but policies prohibit this, since buying a specific company's stock benefits the shareholders of that company.
This would be a huge conflict of interest.

Another answer by Paul Mulwitz,  an online commentator, says “If the government bought ownership in private companies they would no longer be private companies.  “

A good example would be if the US government invested in Apple computers.  Would it act against the company in case of a violation?
There would be a conflict of interest.

Side note, What does the government invest in?

According to the CBO (https://www.cbo.gov/publication/55375) in 2018, the federal government spent $492 billion on investment—for physical capital, education and training, and research and development—which represented 12 percent of federal spending and 2 percent of GDP.


Can the Income Consumption Curve have a non smooth shape? Can the Income Consumption Curve have a shape that is kinked?

An easy example:
When the utility function is
$$
U(x,y) = \ln x + y
$$
and the prices are
$p_x = p_y = 1$, the IOC is kinked at income level $I=1$:
$$
(x,y) = \left\{
\begin{array}{ll}
\left( I, 0 \right) & \text{ if } I \leq 1 \\
\left( 1, I-1 \right) & \text{ if } 1 < I
\end{array}
\right.
$$

A more complicated example:
When the utility function is
$$
U(x,y) = \min\left(2x+2y,x+10\right)
$$
and the prices are
$p_x = 8$, $p_y = 6$,
the good $y$ exhibits inferior (and Giffen) behavior. The IOC is kinked at income levels 30 and 80:
$$
(x,y) = \left\{
\begin{array}{ll}
\left( 0, \frac{I}{6} \right) & \text{ if } I \leq 30 \\
\left( \frac{2I}{10} - 6, 8 - \frac{I}{10} \right) & \text{ if } 30 < I \leq 80 \\
\left( \frac{I}{8}, 0 \right) & \text{ if } 80 < I
\end{array}
\right.
$$


Empiric evidence of abundance and post-scarcity either transition to it? How much are concepts of post-scarcity and abundance economics just ideological/idealist or do we really observing their beginnings already?

For example:

healthcare: gets more and more expensive
food: good organic food does not get cheaper
water: not a problem where it is really abundant since centuries. Some lakes are gone however for example to water an agglomeration like Los Angeles.
good air: not abundant in large urban areas, air pollution has arrived even in Germany, a country which has been looking at this for long time
work: try to get a well paid job without advanced qualification
housing: everywhere scarce with exception of deep, partly abandoned rural areas (3D printing can be a solution, but i.e. in Germany not possible due to unmet requirements regarding energy efficiency standards)
education: either not free or of declining quality (i.e. German schools would need billions of investment to catch up)
family/parenting: women are allowed and expected to make career which creates additional pressure if they target both having kids and high life quality

How to recognise then an empirical evidence that we move to abundance and post-scarcity (sounds like promise of communists in old times actually)?

Okay I have done some research.

Possibly, abundance could be available soon along these lines:

organic food - abundance of edible insects and clean meat from meat breweries
housing - abundant through abandoned rural areas and 3D printed homes, water and good air possible available there as well
education - given you are okay with self-education Internet provides enough free/cheap learning resources


What was the reason for a boom on Wallstreet in 1938? What was the reason for a boom on Wallstreet in 1938?

Our reporter in N.Y. said today that this 1. week of April 2020 was the best since 1938.

What was the reason for this rebound in 1938?

There might even be some quantitative analyses on this (which would make a [much] better answer), but the "word on the street" (i.e. popsci explanation) is that after the 1937 recession (which actually dragged into the first half of 1938), the rebound was due to FDR's massive spending/stimulus program.
However, looking at the Wikipedia page on the 1937 recession, the discussion on the 1938 rebound probably cannot be easily disentangled from the disputes on what caused the 1937 recession.
The uncontroversial facts are that

According to the National Bureau of Economic Research, the 1937 contraction, which lasted from May 1937 until June 1938, was America’s third-worst recession of the twentieth century, paling in comparison to the 1920 and 1929 downturns.
A few statistics reveal the severity of the 1937 recession: Real GDP fell 10 percent. Unemployment, which had declined considerably after 1933, hit 20 percent. Finally, industrial production fell 32 percent (Bordo and Haubrich 2012).

The causes for the 1938 rebound are thought to be among the observed associations:

The recession ended after the Fed rolled back reserve requirements, the Treasury stopped sterilizing gold inflows and desterilized all remaining gold that had been sterilized since December 1936, and the Roosevelt administration began pursuing expansionary fiscal policies. The recovery from 1938 to 1942 was spectacular: Output grew by 49 percent, fueled by gold inflows from Europe and a major defense buildup.

Actually disentangling the fiscal from the monetary contributors is probably quite difficult, hence the various theories advanced by various macro schools. It's still an active area of research.
For the (mostly) monetarist view in a quantitative perspective see Irwin (2012). But even he acknowledges that:

Stocks began to recover in April 1938 when the sterilization program was officially terminated but two months before the end of the recession. But here too, it is not clear if the stock market recovery was driven by the end of sterilization itself or by the expectation that the economy would recover.

Somewhat on the other side of the fence, Park and Van Horn (2015):

After implementing the difference-in-difference estimators, we find that the
increases in reserve requirements did not create financing constraints for member banks and lead
them to reduce lending. Therefore, the actions of the Federal Reserve concerning the required
reserve ratios cannot be blamed for instigating the economic downturn of 1937-38.

I haven't read this latter paper in detail, but on a quick scan they note in a footnote:

Many scholars have blamed the premature tightening of monetary policy, fiscal policy, or both
(Fridman and Schwartz 1963, Romer 1992, Eggertson 2008, Velde 2009, Irwin 2012). On the monetary
side, the Federal Reserve doubled reserve requirements, and the Treasury sterilized gold inflows from
Europe to the United States. On the fiscal side, the Roosevelt administration attempted to achieve a
balanced budget by reducing the growth in government spending and increasing taxes. Other scholars have
proposed alternative explanations, such as labor policies and a shift in expectations. Cole and Ohanian
(2001, 2009) and Hausman (2014) argue that New Deal industrial and labor policies raised wages in the
manufacturing sector and stunted economic recovery. Eggertsson (2008) argues that a shift in beliefs about
future inflation and income caused the recession. Mathy (2014) finds that uncertainty regarding fiscal and
monetary policy by the Roosevelt administration, not reserve requirements, induced the recession of 1937.


Departure point for research in economics I hope this is the place to ask this question. I am in the first year of PhD in economics. As most of PhD students in economics, I try to show some economic mechanisms by theoretical modelling in environmental economics.

Most of time, I have a tendency to base largely on other models in the literature. I try to incorporate my idea in existing models but it does not work really well. For those who are in economics, how do you start to model your idea ? Do you start from a really basic model and complexify after ?

Always use smaller models when you can. Typically, you want to show that

surprisingly/interestingly, if we combine A,B in a model, there is an interaction that explains C.

Have the smallest model that you need to make your point (that contains A,B). Additional features are irrelevant to make your point and will only distract you and your audience.

There are many models which are famous for being able to model A, B, or similar. If you need A and C, take a model famous for being good at modeling A, and add feature C. If there is nothing clean (any model that has A, also has A2, A3, A4 - which you really don't need), you might be better off writing your own model / simplifying an existing one).

Example

For example,

A: Monopolistic competition is a nice way to have firms with positive profit margins
B: The Calvo-fairy is one way of getting sticky prices in an equilibrium model

If you combine A,B (and a few other basic elements), you can interestingly show an environment with room for monetary policy, the standard NK-model.

Say you want to look at the impact of sticky prices onto unemployment. You could take A,B and add sticky wages and monopolistic competition on the labor supply side. Or, you could start with the Diamonds-Mortensen-Pissarides (DMP) model and extend it with B.

The choice of model depends particularly on

Which is the easier choice (certainly the first one)
What is the mechanism you're interested in?

If you believe that workers really are setting the wage and there is some stickiness in their ability to do so, (i) is the way to go. If you believe it is important that employment comes after some matching-period, and wages are set through bargaining from both employers and employees, extending DMP would be a better way.

Fundamentally, if you believe that you could use DMP, but it has some clutter that you don't need, get rid of that first, and then add your price-stickiness.


Applied Chaos to Economics Just a question to satisfy my Mathematical itch, but is there anything in Economics that uses Chaos Theory from Math?

If you're into growth economics the Nonlinear Dynamics in Equilibrium Models (Eds. Stachurski, Venditti, Yano) collection might be an interesting read.

Hommes' book Behavioral Rationality and Heterogeneous Expectations in Complex Economic Systems seems to be nice fit as well.


Show that conditional variance of error in linear probability model is heteroskedastic? I have a problem that asks me the following:

" Consider the linear probability model, in which we specify the
regression equation to be linear in X,
E(Y |X = x) = Pr(Y = 1|X = x) = x'β
We can accordingly express the regression equation by Y = X'β + e with
E(e |X = x) = 0 for all x. Show that the conditional variance of e
given X = x depends on x, i.e., e is heteroskedastic. "

Intuitively, I visualise why this is the case - but cannot figure out how to demonstrate this formally. Could someone help?
Thanks in advance!

In relation to the problem of heteroskedasticity in linear probability models, the following Ben Lambert video is a useful link:
youtube.com/watch?v=pgPhbVEbYqw


Indifference curve - Does $dU = 0$ hold in higher dimensions? / Problem of integrability In two dimensions, we have on an indifference curve that $dU=0$.
Does this apply to indifference objects in higher dimensions?
I was thinking that if $dU > 0$, then one is moving to a higher indifference curve/object
My Macroeconomics professor, in the first week of class, gave a microeconomics review. I asked if $dU = 0$ in higher dimensions. He said he would answer the question next time, and during the next class, he said it may not hold true in higher dimensions because of the problem of integrability.
I asked another economics professor in the department who said that $dU=0$ holds by definition of indifference curves/objects.
What is this problem of integrability, and what does it have to do with indifference curves?
Is it this one?
I've taken 2 courses of real analysis, 2 on probability theory and 2 on stochastic calculus (and 4 on statistics), but the mathematics I've encountered in economics is only up to basic linear algebra and separable ordinary differential equations (Actually the linear algebra's mainly just matrices. I hardly recall learning concepts like 'kernel' or 'eigenvalue' in economics, though I have learned uses for both in finance).

Seems to me $dU = 0$ is true by definition unless $dU$ is not defined

because the function $U$ is not differentiable in some variable.
E.g. $$U(x,y) = |x| + y$$
because there are a countably infinite number of dimensions but the partial differentials are not always absolute convergent and hence cannot be summed up. E.g.: $$U(x_1,x_2,x_3,x_4...) = x_1 - x_2 + x_3 -x_4...$$
because the dimensions have a larger than countably infinite cardinality. I have never seen this in micro but it is theoretically possible. E.g. expected utility over continuum states.

Edit:
This seems to offer an extremely thorough walkthrough of the integrability problem in $n$ dimensions.


When do the curves touch the axes and when don't they? The Demand Curve
The Supply Curve
Monopoly: How to Graph It

In videos (1) and (2), we see that the supply and demand curves do not touch the axes.
In (3), we see that the demand curve touches the Y-axis but doesn't touch the X-axis. MR curve touches both axes. On the other hand, MC and ATC curves do not touch any axis.
When do the curves touch the axes and when don't they?

Broadly, the answer to your question is it depends on the context. Generally, if you have some sort of functional form for the curves, you can tell whether they touch the axes by seeing if there is an intercept on either the P or Q axis (set P = 0 to see if there is a Q-intercept, and vice versa).
So, for example, if you're working on a monopoly problem that assumes a linear demand function of the form $Q_d = a - bP$, the demand curve will intersect the P-axis at $P = a/b$ and the Q-axis at $Q = a$.
It's pretty standard to assume that Q is never negative, so you'll generally never see any curve go to the left of the P-axis. For some curves (like supply), it doesn't make sense for the curve to exist when P is negative, so those won't go below the Q-axis, while for others (like MR), that can still make sense.
But, if you're just doing a general analysis to see what happens conceptually when, say, demand shifts to the right, or supply shifts to the left, then it's irrelevant whether the curves intersect the axes or not. If you don't know that a curve crosses an axis (like from the functional form), it's usually best not to assume either: don't assume it crosses, but don't assume it doesn't cross.


How would Greece "temporarily" leave the Eurozone? Amongst the negotiations between Greece and the Eurozone leaders, there currently exists the possibility of Greece leaving the Eurozone for five years.

Does this imply Greece would have to use a different currency for only the next five years?

There´s several possibilities, but they are all speculative.

My guess is that its not too hard to tell a story like this one: They could leave the monetary union, declare all local deposits and debts to be in drachmas and then move on, printing drachmas and taking them in for tax payments. Later on, when the economy is growing and the fiscal deficit has become manageable, they would apply to be part of the Eurozone again.


GDP Income Approach by industry: Public Administration calculation? How is Public Administration generally considered when looking at GDP Income Approach by industry?
Is remuneration of employees the main factor considered, since there is no Operating Surplus?

I am trying to understand the key principles of such calculations, rather than detailed mathematics. Thanks.

Income approach will sum all gross profits, rents, interest, wages and indirect taxes minus subsidies across the economy. If you want to separate GDP by industry then for public administration you just sum all of the above for its category.
Public administration includes among other things:

Services like transportation, maintaining law and order, road construction, police, jails, tax exemptions, medicare, social security,

Some of the above won't generate profit but some can (for example public transportation). The same holds for interest, rents, wages and so on. For GDP in public administration you just sum gross incomes in this category.


Long term trade data request Can anyone recommend a resource for very long term trade data? (1500-2014). I have looked and found bits and pieces here and there but haven't come across any single data-set covering all of it. I am thinking of mashing my own together but I really do expect it to have been done already.

Max Roser (2014) – ‘International Trade’. Our World in Data provides data on overall international trade growth during the requested time period, citing  as their sources:

International Historical Statistics (by Brian Mitchell)
Correlates of War Bilateral Trade (as mentioned in the comments)
The Maddison Project (which I love)
The Rise and Fall of World Trade, 1870-1939 (2003)
The contribution of intercontinental trade to Europe’s expansion (O'Brien 1982) (Which I could only find a discussion of)

and many other sources...

I also enjoyed Trade and Empire, 1700-1870 and Sailing Away from Malthus: Intercontinental Trade and European Economic Growth, 1500-1800

Hope those help!


Supporting Hyperplane Theorem and quasiconcave utility function My notes says that if $u(.)$ is strictly quasiconcave and differentiable, by the supporting hyperplane theorem, there exists $p >>0$ and $w \geq 0$ such that $ x = x(p,w)$ $\forall x$. I am having a little trouble understanding this. Here's how I think:

$u(.)$ quasiconcave,so the set $X = \{x \in R^L: x  \succeq x_0\}$ is convex. We also know that $u(.)$ is differentiable, and thus continuous, so $X$ is closed. Thus, $x_0$ is on the boundary of $X$. Then according to the theorem, there is some $p$ such that if $x \succeq x_0$ then $p.x > p.x_0$ This means that with this $p$ and $w = p.x_0$, $x_0 = x(p,w)$.

Is my understanding correct? In addition, if the set $X$ is strictly convex, does that mean that theorem is now "if $X$ is a convex set and $x_0$ is a point in the boundary of $X$ there must exist a $p$ such that $p.x > p.x_0 \forall x \in X$ and not $\geq$?

This problem is quite specific to economics. The correct statement is:

Proposition
If $u(\cdot)$ is quasiconcave, strictly increasing, and continuous, then $\forall x$, there exists $p \gg 0$ and $w \geq 0$ such that $x \in x^*(p, w)$, where $x^*(p, w)$ is the Marshallian demand correspondence.

Proof

Quasiconcavity of $u$ means the upper-contour set $\succeq\!\!(x) = \{x': u(x')\geq u(x)\}$ of bundles weakly preferred over $x$ is convex.

By continuity of $u$, $\succeq\!\!(x)$ is closed.

By strict monotonicity of $u$, $x$ lies on the boundary of $\succeq\!\!(x)$.
Consider the supporting hyperplane $p\cdot (x' - x) = 0$ of the closed convex set $\succeq\!\!(x)$ at boundary point $x$ with normal vector $p$.
Since $u$ is increasing, then we can take $p \gg 0$.

Since $\succ\!\!(x) \subset \{ p\cdot (x' - x) > 0 \}$ (general relationship between the interior of a convex set and a half space given by a supporting hyperplane),
$x \in x^*(p, \,p\cdot x)$. $\Box$

Differentiability is not needed. If $u$ is strictly quasiconcave, the Marshallian demand correspondence is a function, and $x = x^*(p, w)$.
The argument above also tells us that $x \in x^*( p, \, e(p, u(x)) )$, where $e(p, u)$ is the minimum expenditure required to achieve utility level $u$ given price $p$.

Questions

Q "...$x$ lies on the boundary of $\succeq\!\!(x)$..."

A
By definition, $x$ lies on the boundary of $\succeq\!\!(x)$ if every open neighborhood of $x$ contains some $x' \in \succeq\!\!(x)$ and some
$x'' \in \prec\!\!(x)$. If $u$ is strictly increasing, this is clear. Every open neighborhood of $x$ contains some $x' \gg x$ and some $x'' \ll x$.

Q "Since $u$ is increasing, then we can take $p \gg 0$."

A
Suppose $p \geq 0$ but has a zero entry, say the first one. Let $e_1$ be the standard basis vector with 1 in the first entry and zero elsewhere. Then $x + \alpha e_1$ lies in $\succeq\!\!(x)$ for any $\alpha \geq 0$, since $u$ is increasing. Strict quasiconcavity of $u$ then implies that $x + \alpha' e_1 \succ\!\!(x) $ for some $\alpha' > 0$ (take a convex combination on this half line). This means the plane with normal vector $p$ cannot be tangent to $\succeq\!\!(x)$---this plane intersects the interior $\succ\!\!(x)$.


What does it mean to make an identification assumption? Trying to understand this problem:

  Suppose you had access to a dataset that follows individuals from
  adolescence throughout adulthood. Each year, you observe earnings,
  educational attainment, health, and marital status.  Suppose you were
  interested in seeing how marriage causally affects the earnings of
  men. Using the described data, how would you examine this question?  What
  would be your identifying assumption?  How could you assess the
  plausibility of this assumption?

First I'm trying to understand, what is an identifying assumption? I think it's the assumption you test that tells you whether there was a causal relationship or not. Is that right?

And my first thoughts on answering the homework problem are these:

I would have to determine that income and marriage aren't simultaneously determined, reverse causal, or both influenced by the same variable. So creating a counterfactual group (unmarried men) and matching with married men could set up a good difference in differences.

But how to assess the plausibility of this assumption? I usually just plug numbers into the computer and don't care about plausibility. What makes an assumption more plausible in econometrics?

Identifying assumption: assumptions made about the DGP that allows you to draw causal inference. E.g. exogeneity assumption for IV, parallel trends assumption in diff-in-diff.

Identifying assumptions (lack of endogeneity in general) can never be
statistically confirmed (a non-reject is good, but it's not confirmation). So assessment of plausibility consists of empirical arguments based on what you know about the DGP.


Explaining fluctuations in inflation rate I have been tasked to explain the changes in economic performance of a particular country as part of my class assignment. In particular, I need to explain the changes in the inflation rate of Malaysia over the past 10 years. The general trend seems to be that over time, the fluctuations in the rate of inflation has become smaller, maintaining at 2-4% in recent years. However, there is this large fluctuation in the period from 2008 to 2010. I am quite sure this has got  to do with the Great Recession of 2008. However, I am not quite sure what is the connection between a global financial crisis and large volatility in prices of goods and services.

Given the expectations-augmented Phillips curve, national output which is less than the natural level of output (the level of GDP which is associated with full employment) causes deflationary pressure at an accelerating rate (assuming people's expectations of inflation is last period's inflation rate).

The financial crisis of 2008 was caused by a credit-driven asset price bubble. This was caused by financial institutions who invested in assets that were at the time priced at a value greater than their fundamental value. By holding these assets that were rising in price, they were used as collateral and/or used as capital buffers in order to make leveraged investments on these same overvalued assets. Causing a feedback loop, as these leveraged investments created a further increase in demand for these assets (raising their price, once more) which caused financial institutions to make further lending on these assets, which drives the asset price higher, and so on.

When the asset-price bubble "burst" and financial institutions subsequently made substantial losses (as they did not have enough capital to subsidise these losses) they had to cut down on their asset holdings to at least mitigate these losses, which caused a significant contraction in lending to the economy, as these financial institutions were more focused on collecting a large reserve base. A decrease in lending causes a decrease in investment in the economy, and subsequently decreases consumption, hence why aggregate demand decreased and the global economy was facing a period of mass deflation.


How is employment related to aggregate demand and aggregate supply? When we talk about excess or deficient aggregate demand , how does employment suddenly comes ?

In an economic model, we normally have a production function that increases with the amount of labour. Since inherited capital is fixed, in the short run,the only way to increase out (supply) is via increasing the amount of labour employed. The real world is somewhat fuzzier; some service industries (like software) can have greater sales without increasing the number of employees. However, such behaviour is limited, and greater output is normally associated with more people working.
The relationship between aggregate supply and aggegate demand somewhat depends on prior economic views. To summarise the Keynesian view, if aggregate demand rises (or is expected to rise), firms will increase output (hiring more labour) to meet expected increased demand.


Help with Monopolistic Competition Proof, Prove Love for Variety I need some help with a proof.

  Assume η = 2 and there are just two goods.  Verify that the following utility function exhibits Love for Variety tastes, show that:

  u(λa + [1 − λ]b, λb + [1 − λ]a) > u(a, b) for 1 > λ > 0

  Additionally, I am given the utility function:
  $$
\\u(q_1,q_2, ...q_n) = \sum_1^N \sqrt[η]{q_i}\,
$$

In the lead up to the question, I am given a different problem to prove that should help me solve the above one.

It uses the same utility function, and I have to prove that the consumer wants a variety of two firms, rather than just one firm, I think I figured it out but I don't know how to apply what I did in the above proof, I have to prove that sqrt(x) + sqrt(y) > sqrt(x + y):

$$
\sqrt{x} + \sqrt{y} > \sqrt{x+y},
$$
$$
(\sqrt{x} + \sqrt{y})^2 > (\sqrt{x + y})^2
$$
$$
2\sqrt{xy} + x + y > x + y
$$
$$
2\sqrt{xy} > 0
$$

Any help is sincerely appreciated.

You have

$$ \begin{align} u(\lambda a + (1 - \lambda) b, \lambda b + (1 - \lambda)a) &= \sqrt{\lambda a + (1 - \lambda)b} + \sqrt{\lambda b + (1 - \lambda)a} \\
&\geq \lambda\sqrt{a} + (1 - \lambda)\sqrt{b} + \lambda\sqrt{b} + (1 - \lambda)\sqrt{a} \\ &=  \sqrt{a} + \sqrt{b} \\ &= u(a, b) \end{align}$$

The inequality in the second line follows from Jensen's inequality for concave functions. I don't think you need to prove Jensen but you can even do that moderately easy with the AM-GM inequality if you want to.


Why marginal benefit is decreasing as more and more pizzas are being produced? I'm taking one of my initial courses in Economics on my own and currently reading Economics by McConnel, Brue and Flynn. On the page 13, the book is trying to explain about Optimal Allocation. They are giving example of production of pizzas and robots, here is the table:

A, B, C, D, E are the possible alternatives of production when resources are allocated accordingly. Now, the book asks "of all the attainable combinations of pizzas and industrial robots, which is optimal (best)?" Then they go on to explain a little bit about marginal benefit and marginal cost and the optimal amount of the activity occurs when MB = MC.
In the next paragraph they write, "Consider pizzas. We already know from the law of increasing opportunity costs that the marginal costs of additional unit of pizza will rise as more units are produced. At the same time, we need to recognize that the extra or marginal benefits that come from producing and consuming pizza decline with each successive unit of pizza. Consequently, each successive unit of pizza brings with it both increasing marginal costs and decreasing benefits."
How marginal benefit is declining as more and more pizzas are produced? Increase of marginal cost is understandable as more and more robots are being sacrificed for successive units of pizza, but won't more and more pizza gonna fulfill more and more satisfaction of people? Why marginal benefit is decreasing? Does it have to do with supply and demand (more pizzas means lesser will be its price)?

You can think of it as the marginal benefit per person. The first piece of pizza you eat is amazing, it has a very high marginal benefit. But say you eat five whole pizzas in one sitting and then are immediately  offered another slice. That next slice doesn’t seem so appealing, does it? You’re already full and starting to get sick of it. That slice has a low marginal benefit. Certainly lower than that first slice. You can also think of this as a continuous process (i.e the second slice is a little less satisfying than the first, and the third is a bit less satisfying than the second and so on).
So, as the total consumption of pizza increases, the marginal benefit (i.e. the benefit of the next unit) gets smaller.


Representing preference orderings over a finite set of outcomes by two payoffs I have read the following statement and I am having difficulty understanding the second part:

  Any set of preference orderings over a finite set of outcomes can be represented either by deterministic payoffs, one for each ordinal rank, or by only two payoffs, if the latter are stochastic.

I get how it can be represented by deterministic payoffs but I do not see how it can be represented by two payoffs if they are stochastic.

In hoping that someone here gets it, thanks in advance!

Say you have preference over $N$ deterministic outcomes, say $N$ bundles of goods, with $1\succ 2\succ\cdots\succ N$. The usual way to represent this preference is by assigning utility numbers $u_i\in\mathbb R$ to each bundle $i$, such that $u_1>u_2>\cdots>u_N$.

In contrast, you can also interpret the "outcomes" as lottery tickets that pay either a high payoff (say $\$1$) or a low payoff (e.g. $\$0$) with varying probabilities. So each lottery $L_i=(p_i,1-p_i)$ is a distribution over the two payoffs, where $p_i$ is the probability that you get $\$1$ and $1-p_i$ is the probability of getting $\$0$. Thus, by choosing $p_i$'s that satisfy $p_1>p_2>\cdots>p_N$, you have a preference representation over the $N$ lotteries in the expected utility framework.


Why don't economists do regression diagnostics? There is a lot of talk about regression diagnostics in tutorials on the web, but then in economics research papers nobody actually reports residual plots, collinearity checks etc. Is there any reason for this?

To start with the question in the title:

Why don't economists do regression diagnostics?

People do regression diagnostics. I don't know of any respectable researcher that would not perform regression diagnostics and virtually any paper will have hints that the regression diagnostics was performed. For example, in tables with regression results you will find remarks on White or HAC errors being used to either correct for heteroskedasticity or autocorrelation or both, or references to corrections for cross-sectional dependence etc.
Only very unscrupulous scholars would make claims about these issues being/not being present without some testing.  So scientists (or at least the good ones) always perform regression diagnostics.
To address the question in the body:

in economics research papers nobody actually reports residual plots, collinearity checks etc. Is there any reason for this?

Yes, almost all scientific journals have very strict page limit of between 30-60 pages with most journals having page limit around 40 pages. In addition shorter articles are often more preferred and attract wider readership because people usually prefer to read shorter papers. Also, note that page limits are usually inclusive of list of references which often can eat up another 1-5 pages and also all other stuff. Only online appendices are excluded from page limit.
Now documentation of regression diagnostic can easily eat up 10 pages if you want to do it properly with all the plots (or even more). Moreover, regression diagnostic is not of much interest in itself. You preform it in order to know how to properly specify your model or what identification strategy to use. Once you figure that you just use the appropriate model, so by itself regression diagnostic has little value for reader as it carries very little information about research result. As mentioned in the first part of the answers people will still mention in their paper that there was autocorrelation or heteroskedasticity and how they corrected for it (and so on for other problems), so there is not that much point in additionally wasting space in the paper on showcasing all the auxiliary diagnostics. Any mistrustful researchers can just request their data and rerun that diagnostic themselves.
Consequently, the reason for that is simply that there is not enough space for it in the paper, and because you always have to economize on the space given. If you would really want to do it, it would usually end up eating 1/3 of a precious space, You would be surprised how common problem it is for researchers to actually fit their research in the page limit. Often you will be forced to relegate even main derivations to online appendices just to fit in the limit. In the end anything that is not of great importance to support or interpret the main result will simply not make the cut.
As mentioned in the comments this can sometimes cause issues with reproducibility, but nowadays the solution to that is that journals require scholars to post their code that was used to derive results (where you would find also regression diagnostics) rather than actually report it in the paper, for the reasons mentioned above.


How does this company gain from economies of scale? Given this story, I am (my younger brother is) asked why (rather than how?) a particular company Pepper plc is likely to benefit from economies of scale.

In short, Jo has a shop that sells electrical goods made by Pepper plc, a large-scale business. Nearby, many people are unemployed so they can't really buy new stuff. However, they might be able to pay to repair their old stuff.

What exactly is the relevance?

Economies of scale is, from what I vaguely remember from introductory micreoceonomics (if I remembered, I guess I wouldn't be here) and understand on Investopedia, an advantage that comes from more production namely that if more of a particular product is produced, but only up to a certain point, any particular unit would cost less.

This is because fixed costs per unit decrease with more units, again, only up to a certain point.

Help please?

Note that for some reason we are talking about Jo's shop while we are asked about Pepper plc.

For reference, here is the whole story:

The story (and Jo) have basically nothing to do with the benefits Pepper plc will get from economies of scale. As you have stated economies of scale means that the average cost (cost per unit) is less if you produce in large quantities.

An example: Assembling a car with drills and screwdrivers is really difficult and time consuming but a robotized assembly line can do it quite quickly. However, the assembly line costs a lot of money so it will only pay off if a lot of cars are produced.

Since Birmingham, where Pepper plc. is located, is a large city it has a large market for electronic consumer goods. Therefore Pepper plc. can sell a lot of these goods, hence it has reason to produce in bulk, so the unit cost is less. Thus the company may sell its products cheaper or have a higher profit. (This depends on the market environment.)


Economic Theories for the creation of a new or separate Industry? Hey i'm doing a paper on the creation of an industry that has spawned from the another industry. I was wondering if there was particularly any interesting economic theory i should look at.

Some of my ideas For example because of the inherent social values of society demand is formed for newer services not traditionally offered by the industry creating a niche market segment. To which i guess i can talk about utility maximisation. And that's about how much i have so far.

Have a look at monopolistic competition. It basically details how many industries can find their own niche in a differentiated product market. Some prominent papers in the subject:

Dixit and Stigliz: Monopolistic Competition and Optimum Product Diversity
Krugman: Increasing returns, monopolistic competition, and international trade
Salop: Monopolistic Competition with Outside Goods


Calculate supply function based on production or cost function Q1: A company has the following production function:
$$f(x_1,x_2) = 2x_1 + x_2$$.
The factor prices are $w_1=4$ and $w_2=3$. Calculate the company's supply function.
Q2: A company's cost function is
$$C(y) = y^2 + 1$$
Calculate the company's supply function.
Unfortunately, I don't understand how the supply function can be calculated based on the production or cost function. I would be very grateful for solutions.
Thank you very much!

Q1
This is not a straightforward problem. Two things to note:
First, the production function is linear in the inputs. This means that their marginal products are constant, and so are their marginal revenue products (presumably the firm is treated as a price taker in the output market). This implies that if price is sufficiently low, then production will be zero.
Second: the production inputs are not complementary, production can happen using both or either one of them.
The profit function is
$$pQ - C = p(2x_1+ x_2) - 4x_1 - 3x_2 = (2p-4)x_1 + (p-3)x_2.$$
From this we see that
$$p < 2 \implies Q = 0$$
because with any choice of inputs the firms will incur losses.
At exactly $p=2$, the firm can have zero-profits if it uses only input $x_1$ for any output level, so here
$$p=2 \implies Q = {\rm indeterminate.}$$
"Indeterminate" in the sense that it could be zero, or any positive quantity, or even "infinity" (see below) - the firm is indifferent between these choices.
Suppose now that $p>2$.
If price is $2 < p \leq 3$, the firm has an incentive to use only input $x_1$, because using also input $x_2$ will incur some loss, while it can use only input $x_1$ and have profit for every output unit it produces. And then, the more it produces using just $x_1$ the more profit it has. So here
$$2 < p \leq 3 \implies Q = \infty$$
Certainly, one could wonder whether this is meaningful, since
a) there is nothing infinite in this world and
b) as the firm produces more and more output wouldn't that eventually push the price down? How much of the good do consumers are willing to buy after all?
These are valid remarks, but the solution that the supply function will be "infinite" indicates the profit-maximizing tendency of the firm, not what will actually happen in the real world.
If $p>3$ the conclusion as regards the supply function does not change. In theory, the firm can here use a combination of both inputs, but because the marginal profit of $x_1$, $2p-4$ is always greater than the marginal profit of $x_2$, $p-3$, for these range of prices, the firm will here too want to use only input $x_1$ for its "infinite" supply.


Is consumer surplus subjective? The producer surplus is objective because the it is the total revenue minus the total variable cost. For example, if the producer sold 100 goods at 5 each, and the total variable cost was 300, then his surplus is 200. The total revenue and variable cost is object because it is numerical, a seller can not change these numbers based on his own perceptions or feeling.

But the demand curve is different from consumer to consumer, the consumer surplus is defined as The difference between the value that a consumer places on units purchased and the amount of money that was required to pay for them. The consumer places on the good is entirely subjective, therefore is it correct to say how big your consumer surplus is entirely up to the individual consumer? And even for the same consumer, the consumer's value placed on a good can change from time to time, for example, the value I place on going to see a movie on a date with a possibility of getting laid later that night is much higher than the value I place on going to a movie by myself even thought the product is exactly the same. But my two consumer surplus would have a enormous difference.

Yes it is subjective. But subjective valuations are where demand curves come from (at least for final goods and services). Consumer surplus is simply a measurement of aggregate willingness to pay so it is subjective (like utility) and measured in currency units (unlike utility).

For example, if a movie ticket is for sale for ten dollars and you'd pay up to 15 dollars to see it then your consumer surplus is five dollars. This valuation is purely subjective. Another consumer could have a different maximum willingness to pay for the ticket. If you thought the movie was going to be less entertaining or had something else fun to do the maximum you'd pay would be lower and so would the consumer surplus.

One area of this that once confused me is the units. Utility functions typically are discussed as though they were in units of utils but utils cannot be compared across people. However, willingness to pay, which is an implication of the budget constraint and preferences implied  by household utility functions, is measured in currency and can be compared across people. That is, it is sensible to say "you would pay more to see Iron Man IV than I would" but not "you would get more utility from seeing Iron Man IV than I would".

So it isn't exactly as @Kitsune says, that consumer surplus is utility minus price. Rather, consumer surplus is willingness to pay minus price, which are both in currency units and can be aggregated over and compared across consumers.


Doubt on a simple problem from Mankiw's Macroeconomics I've just started studying Macroeconomics and I have a quick doubt about the following problem from Mankiw's Macroeconomics 7th edition, page 81:

  Consider how each of the following events is likely to affect real GDP. Do you think the change in real GDP reflects a similar change in
  economic well-being?

  a) A hurricane in Florida forces Disney World to shut down for a
  month.

According to the solution manual, the answer is that "real GDP falls because Disney does not produce any services while it is closed". However, I wonder if it's not possible that real GDP remains constant in that scenario, for instance, if people decides to spend whatever they were going to spend at Disney on other goods and services? Then, if the fall in Disney's production were fully offset by the increased production of substitutes for Disney's services, could real GDP remain unchanged? Is my reasoning correct? Thanks.

In theory, yes. If there are perfect** (and mutually exclusive) substitutes, and exactly the same amount of money is spent on those substitutes (and individuals would not have spent that money otherwise), then GDP could remain constant.However, even for extremely simple goods, this is unlikely.

However, the question asks how the events are likely to affect GDP. In practice, there are relatively few true perfect substitutes. If people can't go to Disney world, some may opt for less expensive alternatives, like watching a movie. Another consideration is whether or not Disney is obligated to pay staff during the time (probably not, so now there are people who are making less money and buying fewer things), Disney isn't purchasing food stocks and cute teddy bears for its canteens and games, and a host of other effects. The point is, it is most likely to push GDP down.

In this case, I would say the question kind of implies "all else held constant". The key learning outcome here is "When there is a shock, and firms are forced to cease production temporarily, this negatively impacts GDP." This is the basic principal for first year econ. In later years, you will get into general equilibrium, which deals more with the side-effects of such shocks and aggregate micro-decisions.

** Edit: It is technically not strictly necessary for them to be perfect substitutes (see comments below). But in practice (and in the spirit of the first-year level question), shutting down a whole firm/industry will push GDP down. People are choosing between consumption and savings when deciding how to spend their money, between labor and leisure when deciding how to make their money, and taking away a large source of consumption-based utility is likely to ultimately shift choices away from consumption and towards savings and leisure both of which push down GDP in the current period, though savings generally increases it for t+1 (I am not going to get into trade-deficit effects here). But that is a more complex analysis that isn't really the point of the thought exercise in this particular case. Key learning: External shocks that reduce production generally reduce GDP, all else held constant.


What to do for missing points in CPI time series? I am looking at CPI datasets for developing countries which have gaps in them.

For each country I have two time-series with annual averages for years 2000-2013: i) General/Overall CPI and ii) Food CPI. I'm also assuming that Food CPI must have some relationship with the General/Overall CPI since the Food category has its own weight in the General CPI.

Now, I have two types of cases, some such as: http://imgur.com/a/9z7o8#1 where gaps are between values. I'm assuming I can interpolate here, if so, how would I go forward with this? I also have to deal with more complicated cases such as: http://imgur.com/a/9z7o8#0, any suggestions in this case? Would a simple extrapolation even make sense here?

An option for my first case that I read (on BLS) is taking the geometric mean of the year immediately before and after of the missing value. Other people have suggested I should predict the missing values by a simple regression model of the CPI on the GDP deflator for that year (which I do have).

Also, in some cases, gaps in annual averages exist because the monthly data needed to calculate these averages is incomplete. So say I only have 2006 data for Russia for months Jan-June, then the annual average data point is missing in the data series. I assume I can just take a simple average of the available months and impute that for 2006?

Thanks in advance

Statistical Analysis with Missing Data by Little and Rubin is the go-to reference for working with missing data, at least if nothing state of the art is required. In general, this is a complex problem that remains an area of active research. The relatively easy cases are when the data is missing-completely-at-random or missing-at-random. Even among the most basic single imputation methods you have a lot of choices (list from Little and Rubin):

Mean imputation (replace with mean values)
Regression imputation
Stochastic regression imputation
Hot deck imputation (substitute individual values drawn from "similar" response units)
Substitution (not relevant in your context)
Cold deck imputation (replace missing value with constant value from external source like last value)
Composites of the above methods

However, if all the the general price level is what's of interest and not the dynamics of the price level (e.g. because you want a deflator instead of studying inflation dynamics) linear interpolation / extrapolation may be just fine. Fundamentally, since deflation is rare, if prices are 100 at time t and 110 at t+2, realistically prices at t+1 are going to be somewhere in $[100,110]$ and lots of models can get you there.

You can check the within and out of sample prediction quality to asses if your method is a good predictor of the missing prices. Within sample testing could be as simple as asking if the $R^2$ is high of predictive model. Obviously you can do much richer analysis than that. For out of sample testing, consider splitting the sample and calibrating the model only on the first half of the data, then evaluating prediction quality on the second half of the data.


What is an econometrician? According to Wikipedia, Econometrics is the application of mathematics, statistical methods, and computer science to economic data and is described as the branch of economics that aims to give empirical content to economic relations. It sifts through mountains of data to extract simple relationships. Generally for positions like Analytic Consultant, Data Scientist, Statistician, Quantitative Analyst, background in maths, stats or econometrics is required. What separates econometricians in terms of what they learn in school and how they apply acquired knowledge in work? Or do these fields overlap so much that there is not much to distinguish?

An interesting question that leads to a debate among econometricians. Some consider that

Econometrics is just statistics applied to economic problems

  Econometrics is just statistics applied to economic problems—nothing
  more and nothing less. We should probably call it “statistical
  economics,” but I guess people feel that the term “econometrics” has a
  better ring to it. The only cost of using the term “econometrics” is
  that we are sometimes fooled into thinking that we work on a distinct
  discipline, separate from statistics. This is not true.

From John Stachurski at ANU (see his notes p.108 in Econometric Theory freely downloadable)

Others consider that

Eonometrics by no means the same as economic statistics

This quote is from Ragnar Frisch (one of the founders of the Econometric Society) and his Editor's Note on why the Society has decided to establish its own journal, Econometrica.

The key idea is that economic theory is crucial to understand measurement. Neither theory nor measurement on its own is sufficient to further our understanding of economic phenomena. We need both and measurement without theory is unlikely to provide a satisfactory explanation of the way economic forces interact with each other.

Another difference is, as economists, we are biased towards establishing causal relationships. So, this explains our focus on endogeneity issues and strategies of identification.


Textbooks addressing Markov decision processes in microeconomics/game theory/decision theory? I have learned about the Markov decision process (MDP) formalism in the context of machine learning. I know that micro theorists also study MDP's, and agent behaviour in this context (both single and multi-agent I think).

I am wondering if there is a good/standard textbook on MDP's from the perspective of micro theory (game theory/decision theory)?

If not, is there at least a micro theory textbook that heavily focuses on MDP's?

I guess you learned about MDP from Reinforcement Learning since RL tries to solve MDP without parameters.

For MDP without considering Microeconomics, (Indeed MDP is a decision-making process.)

"Markov Decision Processes: Discrete Stochastic Dynamic Programming" by Martin Puterman

If you want an Economics based book,

"Recursive Methods in Economic Dynamics" by  Nancy L. Stokey and Edward C. Prescott

For multi-agent MDP, (there are not many books for this topic specifically  although some Economics books mention the topic)

"Competitive Markov Decision Processes" by Jerzy Filar and Koos Vrieze


Signalling in a moral hazard contract with informed principals (that know their own type before contracting) I was studying Laffont & Martimort textbook for a paper, but their section on moral hazard contract with informed principals assumes that the principal only knows his own type after contracting.
But I need a model where principal knows the type before contracting (probably with signalling issues).
Laffont & Martimort manuscript reads that such contract would be explored in a Vol. III of the textbook, but I think this volume do not exist (as Laffont got cancer and deceased right after the publishing of Vol. I). Is there any other textbook or paper that describes this model?
Thank you.

I'm not sure what exactly you're looking for, but here are some wild guesses:

Bolton and Dewatripont (2005) Contract Theory, MIT Press. [Probably Chapters 5 and 6]
Maskin and Tirole (1990) "The Principal-Agent Relationship with an Informed Principal: The Case of Private Values", Econometrica 58: 379-409.
Maskin and Tirole (1992) "The Principal-Agent Relationship with an Informed Principal, II: Common Values", Econometrica 60: 1-42.
Myerson (1983) "Mechanism Design by an Informed Principal", Econometrica 51: 1767-1797.


What determines if a variable is exogenous or endogenous in a model? Question above, I have a very rudimentary understanding of econometrics.

An endogenous variable is one whose value determined within the model. Exogenous variables are those variables whose values are determined by influences outside the model.


What value do virtual traders of commodity add to the market? Many if not most companies trading in commodities are only trading them on paper. They will not use the commodity they are buying and can not take deliver of the physically commodity.

What value do these investment brokers/banks bring to the market? Specifically since they are not able to take delivery, even for storage. What is the economic rational that would have governments allow and promote this type of business activity?

There are various important social benefits of commodity trading even just on paper. The main ones are risk management, hedging, providing liquidity and secondary market, and price discovery.

For example, both producers and customers of commodities can use future market to hedge risks of adverse price movement. For example, in market for potatoes the potato store always faces risk that the price of potatoes will increase and conversely the potato farmer faces risk that the price will drop. This could be for example due to unpredictable weather patterns which can cause supply to vary from year to year.

One way how to avoid sudden price swings to make a future contract between farmer and seller of potatoes where the farmer agrees to deliver seller certain quantity of potatoes at per-specified price. However, pricing such future contract requires lot of skill and speculation that most farmers or potato store owners might not have so naturally through division of labor this part of work is outsourced to commodity trader. Esentially - your question is in its spirit the same question as what store adds to the market and why sellers exist and why commodity producers just dont sell directly to consumers and again answer would be division of labor as farmer might not necessary be good seller.

Moreover, most traders dont trade just in one commodity but in multiple so it is easier for them to manage risk associated with the trading the commodities, and it is always socially optimal that the party which has the least costs of managing risks takes the risk from parties which have the higher costs of managing risks.

Furthermore, the traders can also provide liquidity to the market. Again a bank or big financial company will certainly have a comparative advantage to the farmer or store when it comes to providing liquidity to the market and this function is connected to the above mentioned function of hedging and risk management so it makes sense that instead of farmers and stores keeping extra liquidity they outsource this task to the commodity trader.

Having a secondary market where you can sell your commodity is another good thing. For example imagine that potato farmer entered into a contract to sell a certain quantity of potatoes at a certain price. However, later one of the parties wants to back out. They can do so by selling the contract on the commodities exchange. Since the exchange is the counterparty to everybody, the farmer may not even know that the buyer has been changed and vice versa (also note that in some textbooks this is also mentioned as a part of market providing liquidity, but in others the provision of liquidity was used in more narrow sense of providing leverage to the market participants).

Price discovery is another important reason why especially spot markets exists. Especially for very highly perishable commodities it might be very hard for farmer or store to know exactly how to price the goods and hence even before advent of modern finance sent some representatives to market to haggle the price for them in one place so they dont need to leave their work to do that (That farmers do this is even mentioned in Plato's republic - so really spot markets existed even in ancient times albeit in less sophisticated form).


Isn't the parameter A denoting technological progress from Cobb-Douglas already included in alpha and beta? Does it not follow that if capital is better performing than labor it would be used more frequently? What exactly does parameter A actually mean, then?

The word technology might have slightly different meaning depending on a field. For example, Varian in his Microeconomic analysis (3ed) calls the whole production function technology. He literally writes on a first page of his book:

The simplest and most way to describe technology of a firm is the production function

However, in macroeconomics it is often equated to the $A$ parameter (see Romer Advanced Macroeconomics chapter 1 where technology growth and growth of $A$ for Cobb-Douglass function is used interchangeably throughout the chapter and also elsewhere in the book).
In the broader (Varian Meaning) you can consider alpha and beta parameters to be part of technology or determined by available  technology (since whole production function is by definition in the Varian meaning determined by technology) but they are not technologies themselves per se (just their component). Rather they are output elasticities and in addition their sum tells you if there are increasing, decreasing or constant returns to scale, but technological progress does not necessarily mean that firms production will have different returns to scale or that output elasticity increases or changes in any way. Also, note these are virtually always considered to be constants.
In the macroeconomic sense they are not technology and the technology would be solely captured by $A$. In macro sense the $L^{\alpha}K^{\beta}$ would be some sort of ‘vanilla’ production which is then augmented by technology parameter $A$ (which could by the way also enter in a way that would augment only labor ($(AL)^{\alpha}K^{\beta}$) or only capital ($L^{\alpha}(AK)^{\beta}$) or also both ($AL^{\alpha}K^{\beta}$)).
So depending on which subfield you look at the terminology will differ, but I can’t recall ever seeing in the literature someone claiming that alpha and beta are the technology, at best you can argue they are determined by technology. Also depending on which field you specialize in you will want to follow the preferred terminology in the literature.


Why do all countries recognize foreign wealth? Recently I learned that by 2016 that 1% of the population will have 50% of the worlds wealth. That means that more than 50% of individuals actually has less than he would in a totally fair economy.

Of course, money is a social construct. If someone does not acknowledge others wealth, that wealth might as well not exist (at least for the purposes of that relationship). So when enough people share this attitude, then all the wealth that exists might as well not exist, and a sort of "reset" happens?

However, I don't imagine it's that simple, especially for individuals, who are unlikely to be self-sufficient without making purchases using money. However, on a country level, there seem to be a number of countries that would benefit simply by turning inwards and actively failing to recognize foreign wealth. Notably, I recently watched a documentary on Lake Victoria fishing which had communities unable to eat any of their own fish for it was "better economically" to export it. And so they lived in poverty and starvation.

Well that just seems silly to me. So my question is, could a country like Tazania just turn inwards (don't recognize the concept of wealth with respect to other countries) and be self-sufficient (and thus, it seems, actually be able to use its food to feed its own people)? Even if just temporarily to build up important things like infrastructure education before joining the world economy again. If so, what are the caveats? If not, what are the factors stopping it?

Countries do not just stop recognizing foreign wealth because there are two kinds of wealth: real assets, and claims on the production of others; the values of both of these types of wealth are not determined by consensus, but rather by the use or pleasure one can derive from them.

To the first type— real assets are stuff like machines and cars and homes and all sorts of things that you can touch and which we value for one reason or another. The answer to your question as pertains this category is easy: you can "not recognize" my car as wealth all day long, but that won't affect its value to me or anyone else one bit.

To the second type— claims on the production of others come primarily in the form of money, but also in the form of non-money debt and equity. I will skip over non-money debt and equity, as they both provide a claim on a future stream of money, so their value hinges on the value of money. Now, rephrasing your question slightly, we arrive at: why is a foreign country's money valuable? Or, more specifically, why is a foreign country's money valuable in a way that is not subject to one's recognition of it?

The answer to this is simple (and a fundamental concept in international economics): a country's money is valuable to the extent that you want to buy that country's stuff (or buy claims to their production, i.e., debt and equity). This is why countries with economies based around commodity exports see their currencies fluctuate with the value of those commodities (so-called "commodity currencies")— because when demand for those countries' production increases, the values of their currencies increase. So— one can go all day not recognizing the value of another country's money, so long as one doesn't want to buy that country's stuff.

I will confess to not being terribly familiar with the situation you describe in Tanzania, but I would suggest simply that the locals who choose to sell their fish rather than eat them are likely to have a much better understanding of the implications of doing so than you or I. I would suppose that they're selling their fish because they receive something else in exchange (money), which they turn into something of greater value to them than the fish they sold. Let's say that what they receive in return is gasoline, for use in boat motors (which are essential to catching fish), generators that power lights and pumps to provide clean water, and inefficient and dirty cooking devices (that are nonetheless better than the alternative, which would be attempting to scavenge firewood). Are they better off with fewer fish and more gasoline? Yes, otherwise they wouldn't make that trade. Would they be better off if they didn't sell most of the fish and get gasoline in return, or would they be more likely to "build up important things"? No, almost certainly not— otherwise they would not sell their fish. Unless the Tanzanians you describe are being forced to trade, it's a safe bet that they're trading because it is beneficial to them. They're poor, yes— but that doesn't mean they're stupid.


Properties on conditional demand correspondence from the textbook of Mas-Colell et al I have a question on the properties of conditional demand correspondence
Let $z(w,q)$ be the conditional factor demand correspondence, i.e. the solution of the cost minimization problem
\begin{align}
\min_z \quad& w\cdot z \\ \text{subject to}\quad & f(z)\geq q.
\end{align}
In the book of Mas-Colell, Whinston, Green, Proposition 5.C.2 (v) says that

if the set $\{z\ge 0 : f(z)\ge q\} $ is convex then $z(w,q) $ is a convex set.

Also, in the same property, it states that

if $f$ is quasiconcave then $z(w,q)$ is a convex set for every $w>>0$.

How can I prove these two statements? I would like to understand these two properties. Thanks a lot.

Let $z_1$ and $z_2$ be $\geq 0$ and solution to
$$\min_z \{w^\top z\lvert f(z)\geq q\}$$
then clearly $f(z_1)\geq q$ and $f(z_2)\geq q$ and since $\{z\geq 0\lvert f(z)\geq z \}$ is convex it then follows that $z_3 := \lambda z_1 + (1-\lambda)z_2$ must satisfy the constraint $f(z_3)\geq q$.
Since $z_1$ and $z_2$ are both minimizers it cannot be the case that $w^\top z_1 \not = w^\top z_2$ rather it must be the case that $w^\top z_1 = w^\top z_2$. This implies that $w^\top z_3 = w^\top(\lambda z_1 + (1-\lambda)z_2) = \lambda w^\top z_1 + (1-\lambda) w^\top z_2 = w^\top z_1$ hence $z_3$ is a minimizer.
Since $z_3$ is minimizer and satisfy constraint it must be in $z(w,q)$ which therefore must be convex set.
If $f$ is quasi concave then by definition $\{z\geq 0 \lvert f(z) \geq q\}$ is convex and therefore using the above argument implies $z(w,q)$ is convex.


Samuelson Acceleration Model Question I first posted my question in the wrong forum (I did not know that there was an economic forum now) so I want to apologise for that by User Ben Bolker and User Robert. Also special thanks to User Robert who gave me the information with the econonomics forum!

So my question is about the Samuelson acceleration model. I am trying to help a friend of mine solve this question.  I am not an economic studied person. I attached the question and my answers and conclusions. Maybe some of you can give me a little bit of help. In the first case, I did interpret the whole topic wrong and was confused because of the difference and thought this should be possible with an derivation (which was absolutely wrong, in my opionion now). I found an old analysis economics book and there were some interesting facts about the question (I also attached these facts).

The main question is, is it possible to bring the function back to the standard form of an inhomogen linear style with index inversion or something else. You can see what I have done attached, but I could not change the following from t-1 to t+1 because I did not know how.

Maybe some specialists here can help me.

Thank You!

Cheers

There is nothing more to it than the equation

$$Y_t - (c_y+v)Y_{t-1} = C^a + I^a$$

This is a linear non-homogeneous first-order difference equation, and it is non-homogeneous because there is a non-zero constant, $C^a + I^a \neq 0$.

This is not some "habit in economics", but rather standard mathematical terminology.


Is it possible, that the global warming will affect the growth of the economy? I am wondering if, in the face of the global warming, the long-term passive investments into ETFs are still a good idea. Right know we benefit from the growth of the economy. I assume (maybe that's wrong assumption) that in the big picture the overall growth of economy is fully dependent on the energy, i.e. whether the particular company produces products or provides services you can always show that it needs energy to grow. Global warming seems to significantly affect our energy production and the following global crisis seems to me to be very different than for instance world wars - you cannot stop it by just signing peace documents. I wonder if my reasoning is right and to be honest I hope that it's not.

Global warming doesn't impact energy production in a major way (nuclear plants getting shut down because the cooling water is too hot is a thing, but it's not a major thing). If anything we're building far more energy production (solar and wind) before we ordinarily would have to (plants reaching end of life). If energy consumption went up we would just not close a power station early....

All of the above assumes you're talking about europe/AUS/US. In other continents demand still outpaces production in many places. But that's not a global warming problem, they will happily build coal plants all day long.


What are the differences between cryptocurrencies and digital currencies backed by CBs? Given all the hype around the cryptocurrencies like bitcoin, ethereum, etc., I'm wondering what are the main differences between those and a possible digital currency, backed by a central bank, in a hypothetical 'cashless society'?

Any help would be appreciated.

Two more differences
(1) You can pay your taxes in a government controlled digital currency, and you can't do that in cryptocurrency.  According to Modern Monetary Theory, that is an essential element to the fundamental value of a currency
(2)  even though an individual cryptocurrency may have the feature of a limited supply, there's nothing to stop multiple cryptocurrencies being created, potentially diluting each other's value.  That is not the case with the single currency of the realm.


What does "the event of economic consequences" mean? I read a paper talking about the Operating Cycle. On page 6th, they said:

Sales of assets, no matter how disguised, are one-time events. In
contrast, cycling capital through the cycle and generating cash
contribution margins from operations hopefully is a repeatable event
and the event of economic consequences that justifies the existence of
a firm. It is the well of economic returns

From my understanding, sales of assets above mean that the company sells the timber, or oil, or cash equivalents, and they are one-time events. Then,"cycling capital through the cycle" means dollar leaves cash and go through other asset account, and $1.05 comes back into cash after a number of days. Then "contribution margins" means selling price per unit minus variable cost per unit.
I am wondering why they hope it is a repeatable event, and what does "event of economic consequences" mean in this sentence?

This text is basically about the use of assets. They can be sold once generating some cash or they can be put to use generating cash. The latter can be done multiple times (which is what the repeatability phrase is about), and in the long run should generate more cash than just selling it.
When writing that the latter is the event of economic consequence, the authors mean that this is the process that generates the most money.
Incidentally you seem to be thinking of natural assets, but the authors are thinking of man-made capital assets such as machines or buildings. Those can be put to use.


Why does China buy so much U.S. Treasury debt? What is the reason that China buys so much US debt in form of Treasuries? How does this help the Chinese economy? It seems they are willing to give money to USA so USA economy can function better (more cash more investing in infrastructure).

What is in it for China, holding a bunch of paper yielding next to nothing?

As was said above, buying debt to affect the exchange rate and make Chinese exports more attractive may be one reason to buy these Treasuries. Surely all of these are not reinvested into buying more debt and some of it is put into other civic projects.

The other reason to buy debt is to have a string of payments over time that may become more valuable later on. Since the US is a large nation and powerful nation, China probably feels it is very unlikely that the USA will default, and if they did, that would give China a legitimate complaint against the US, that might help them in foreign relations. It may even be that they want the US to be stable so as not to crash the global economy and so that they can still sell lots of products to the US, so they buy up the debt to keep the USA stable.

The more important part of that whole paragraph though is to have a string of payments. For the same reason that governments like to hold debt even when they have the ability to pay it off, China might find that investing into debt will provide a better rate of return than infrastructure at the moment, and later on, once infrastructure has a better rate of return (capital steady state changes) then they can take a stream of income from interest payments from the US and taxes and then invest into that.

Finally, I couldn't help but notice that you see China as needing to lift itself out of poverty. That may be true, but why would investments into infrastructure be the solution to helping the rural poor--places that don't need as much infrstructure? Most of the poor in China are in rural areas, so there's something to think about.


What will happen to a poor country’s economy if it replaces its entire banking system with the Islamic banking system? I don't know much about economics. So, I am just curious about the Islamic banking system.

What I understand is: I know that the USA is the dominant economy and the USD is the dominant currency in the world both as the reserve currency and the trading currency. So, each and every country on earth is dependent on the USA one way or the other. On the other hand, the banking system runs on interests that cause recession from time to time which affects poor countries.

So, I have the following question:

What will happen to a poor country’s economy if it replaces its entire banking system with the Islamic banking system only? Will it do better, or will it become bankrupt?

I see a lot of research on Islamic banking, but I don't see a lot of studies that speculate on the question framed here. You might be interested in this study where the author claims:

  It would be better if Islamic banks had the opportunity to work as a sole system in an economy. That would provide Islamic banking system to fully utilize its potentials. Studies show that Islamic banks can not operate with its full efficiency level if it operates under a conventional banking framework, their efficiency goes down in a number of dimensions. The deterioration is not because of Islamic bank’s own mechanical deficiencies.  Rather  it  is  the  efficiency-blunt  operations  of  the  conventional  banking  system  that  puts  obstructions to efficient operation of Islamic banks.

However, it doesn't look like these assertions have been proven. For example here is a study that suggests that Islamic finance works best on a small scale as larger-scale Islamic banks seem to have unique instability issues.


Theory of and studies on the long-term effect of governmental redistribution Proposition 28 from this 2000 survey (Fuller and Geide-stevenson 2010) of American economists shows that 49% of American Economics Association members agree, and 31% agree with provisions, that it is a legitimate role for the government to redistribute wealth.

That was an increase over 1990.

Policy beliefs rely heavily on values, but is there substantial theory or evidence showing that the policy of governmental redistribution improves either long-term economic growth or long-term absolute well-being of poor people?

This is a very broad question and no one except the respondents in question know exactly what they believe and why.

However, I suspect one important result in this context is the Second Welfare Theorem.

In simple language and subject to some assumptions:

The First Welfare Theorem tells us that any competitive equilibrium leads to a Pareto efficient allocation of resources.

The Second Welfare Theorem tells us that almost any Pareto optimal equilibrium can be achieved via the competitive mechanism, provided appropriate lump-sum taxes and transfers are imposed on individuals and firms.

The main idea here is that markets lead to efficiency. Thus, no intervention of the government is required. However, a situation where someone holds every good and the rest of the population holds none, is also a Pareto efficient distribution. This distribution can hardly be considered as perfect under any welfare definition. The second theorem helps us here.

The two main issues economists are concerned about in this context are efficiency and distribution. The first is all about not wasting resources and maximizing the total economic pie. The second issue is about distributing that pie. The first theorem tells us that a free market achieves an efficient allocation. The second tells us that we can achieve any distribution we want through transfers without harming efficiency.

It is unlikely that the one particular efficient allocation which results from a free market (out of the endless possibilities) also is optimal from a distributional point of view (and optimal distribution will depend on a society's preferences). Luckily, according to the Second Theorem, we can use transfers to achieve both optimal efficiency and distribution. Hence, it is unsurprising that many economists would be in favor of that.

The controversies start with discussion how exactly to design those transfers. Any economist would agree that lump sum taxes and distribution are optimal. However, these taxes are considered impossible politically, which means we often have to rely on transfer mechanisms that trade-off efficiency and distribution.

About your question "is there substantial evidence showing that the policy of governmental redistribution improves absolute well-being of poor people?": The answer must be yes by definition. If we give poor people more resources it can be safe to assume that their economic well-being is improved.


How does the Fed get money As far as I'm aware, the Federal Reserve has 4.5$ Billion on its balance sheet.

Where did it get the money for buying all those assets?

I understand that it makes money out of interest on the bonds it holds, but where did it get the money to buy those bonds in the first place?

If you read Fed's balance sheet, you'll see a corresponding increase in its liabilities under various deposits. They simply credit the accounts of institutions who sold them the assets.