Answer:
land rents were high because grain prices were high..
Explanation:
grain prices were high because land rents were high.
land rents were high because grain prices were high.
grain prices were high because land rents were low.
land rents were high because grain prices were low.
none of the above
David Ricardo was a classical economist known for various economic theory. Some of his theories include :
- Labour Theory of Value
- Ricardian Equivalence
- Theory of comparative advantage
- Theory of rent
Theory of rents
David Ricardo defined rest as the part of the produce of an agricultural land that is paid to the landowner for the use of the land. He postulated that benefits of an increase in prices of grain accrue to land owners in the form of rent
He used this theory to answer a question that arose during the Napoleonic wars (18.05-1815) when there was a great increase in corn and land prices. The question was : Did the rise in land prices raise the price of corn or did the high price of corn increase the demand for land and led to an increase in the price of land ?
Answer:
A. 6.50 years
Explanation:
Let C represent consumer loans,
T represent T-bonds and
t represent T-bills
Portfolio duration = wC*dC + wT*dT + wt*dt
w = weight of...
d= duration of ....
Find the weights;
Total amount invested = 75 + 39 + 18 = 132 mill
wC = 75 / 132 = 0.5682
wT = 39 / 132 = 0.2955
wt = 18 /132 = 0.1364
Portfolio duration = (0.5682*3) +(0.2955*16) + (0.1364*0.5)
= 1.7046 + 4.728 + 0.0682
= 6.50 years
What is a market that runs most efficiently when one large firm supplies all of the output referred to as? Natural monopoly. A natural monopoly happens when there are high fixed costs or start-up costs when running a business in certain industries. A natural monopoly example are pipelines that run for water and gas. This is because they are expensive to start and run but also extremly necessary and specific to the industry.
It is true that ''In a forecasting model using simple moving average, the shorter the time span used for calculating the moving average, the closer the average follows volatile trends''.
There are three fundamental categories: causal models, time series analysis and projection, and qualitative approaches. The first makes use of qualitative data (such as the judgement of experts) and details about noteworthy occasions of the sort already discussed, and may or may not take historical factors into account.
Although there are many commonly used quantitative budget forecasting tools, in this article we concentrate on the top four techniques: Straight-line, moving average, simple linear regression, multiple linear regression, and straight-line.
The Global Forecast System (GFS) of the National Weather Service and the European Center for Medium-Range Weather Forecast (ECMWF) model are the two most well-known NWP models. The American and European models are other names for them.
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