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Julia Wilson
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According to the research conducted by Halpern, Koren, and Szeidl, limiting imports would not benefit the domestic economy. The article suggests that there is a significant positive correlation between imported inputs and productivity. If one were to model an equation for productivity measure either by increased revenue or quantity, imported inputs are a big factor. The researchers consider the “base case” by setting the level of imported inputs to zero and one hundred percent and then comparing. The increase in productivity is pretty significant: “In our baseline case, increasing the fraction of tradable goods imported by a firm from zero to 100% would increase revenue productivity by 22% and quantity productivity by 24%.” However productivity is measured and all other variables held constant, imported inputs increased productivity by one fifth. This one variable alone has a dramatic effect on productivity. In a productivity equation, the correlation coefficient for the variable representing imported inputs would be high. If the government were to limit imports, this would greatly effect productivity. For instance, suppose we set the imported inputs variable to zero. In the productivity equation, this would eliminate a factor that has the potential to boost productivity by about a fifth. One point that I found particularly interesting in this article was the significance of ownership. Foreign-owned firms benefit from imported inputs much more than domestic-owned firms. If we were to split the imported inputs variable into two variables, we would see that the foreign-owned firms variable would have a higher correlation coefficient in the productivity equation. The researchers found that “firms that have been foreign-owned benefit by about 24% more than purely domestic firms from each $1 they spend on imports.” This is also a significant finding. Foreign-owned firms benefit about a fourth more than domestically owned. Ultimately, it does not appear that limiting imports would benefit the economy but rather hinder growth. Since imported inputs have the ability to increase quantity productivity by 24%, the increase in quantity would probably shift the aggregate supply curve outwards to the right. This shift would most likely lead to a fall in the price level, and cause the consumption variable in the GDP equation in increase.
I think the most interesting part of this letter is that is argues that a balanced budget amendment could lead to negative outcomes in both the short run and long run. (Perhaps if there were short term negative effects that would lead to growth and positive long term effects, this would be understandable. However, this doesn't seem to be the case here.) In the short run, when there is a recession, the government runs a deficit in order to help the economy. However, if the government was unable to implement this fiscal policy due to an amendment, this could make a bad economy even worse: “To keep the budget balanced every year would aggravate recessions.” Additionally, in the short run, a balanced budget could lean in a decrease in investment spending, a key to economic long term growth, as it “would prevent federal borrowing to finance infrastructure, education, research and development, environmental protection, and other vital investments.” This would be very detrimental to our economy’s growth potentially. Also, since the government would no longer be borrowing as much for these investments, what other effects would this have? It seems that a cut in the US’s borrowing would have ripple effects. I image it would hurt other countries’ economies and would also increase domestic unemployment. The main question this article raised for me is: In what other ways would this balanced budget amendment affect the economy? Are there other less obvious negative effects?
Barry Eichengreen’s “Confronting the Fiscal Bogeyman” demonstrates how fiscal and monetary policy are both necessary for our economy. Though we have discussed that in the long-run, the economy can self-correct, Keynes points out that “in the long run, we are all dead” which demonstrates the need for stabilization policy to expedite the correction back to the point of potential output. Eichengreen points out that monetary policy was initially used to correct the sinking world economy by decreasing interest rates. This would hopefully lead to more investment spending, the key to long-term growth, and also open up more jobs (which could lead to more consumer spending). As Eichengreen explains, interest rates could not fall much further without hurting banks; therefore, fiscal policy is necessary too. Government could choose to borrow for investments in society (such as education), or the government could choose to cut taxes in order to increase consumer spending. Although as we have mentioned in class, while a tax cut would mean more money for consumers, they could chose to use the money to pay off debts, rather than spend it. Either way, I think this article does a great job of arguing why both monetary and fiscal policy are necessary for the well-being of our economy. Additionally, this article brings up an interesting psychological point: Why is that budget deficits have such a negative connotation? Budget deficits occur when government spending exceeds tax revenue. Government spending may stimulate the economy, so it interesting that the Germans, for example, have such an aversion to running a deficit. I found this quote from the article particularly interesting: “Adherence to this doctrine prevented postwar German policymakers from being tempted by excesses like those of Hitler and Stalin... The ordoliberal emphasis on personal responsibility fostered an unreasoning hostility to the idea that actions that are individually responsible do not automatically produce desirable aggregate outcomes. In other words, it rendered Germans allergic to macroeconomics.” This suggests that aggregate demand is not always positively affected by individual decisions… Sometimes the government may need to step in with policy in order to get the economy back to potential output.
In relation to the circular flow diagram, Kelley’s article makes a lot of sense. Thinking of a restaurant as a firm, a modest increase in minimum wage would increase a household’s income. This increase in income could either be saved or spent. If the money spent within the market of good and services, this would stimulate the economy. Perhaps the demand for goods would increase or perhaps more jobs would become available due to an increase in demand. If the money is saved, this would increase the amount of money the financial markets have to loan to firms for investments. This also would likely positively stimulate the economy. However, the article suggests diminishing returns to an increase in minimum wage. At some particular wage, a restaurant would no longer be profitable. This could result in laying off workers or an increase in prices. If the prices increase, this could result in a decrease in demand for customers. At some point, consumers would be unwilling to pay significantly more to eat a meal out, rather than at home. However, with a small increase in price (due to an increase in minimum wage), consumers would most likely still be willing to pay a bit more for the convenience and experience of eating out. Although I do wonder that if prices increased, would customers be less willing to tip as much as they previously did?
Krugman’s article, “Structural Humbug Revisited,” demonstrates how it easy to ignore all the evidence. In our book, structural unemployment is defined as “unemployment that results when there are more people seeking jobs in the labor market than there are jobs available at the current wage rate” (208). Structural employment indicates that firms cannot find workers. Certain workers do not have the necessary skills demanded by employers, and therefore, the wages of these positions would increase in order to find workers with these skills. When it comes to structural employment, there doesn’t seem to be a lot that the government can do… However, cyclical unemployment is related to the business cycle. The government can do something to address this kind of employment by encouraging spending in some way. As Krugman argues, we did not see a rises in certain wages; therefore, unemployment during the Great Recession must be cyclical, not structural. While I understand this logic, I do wish Krugman had gone into a little bit more detail in this article as to why the employment must be structural then. Additionally, as we discussed in class, I can see how this “strange consensus [developed] into elite opinion.” I think it’s a rather common phenomenon for people to let their biases and opinion cloud or morph actual evidence. For example, in research, it can be easy to declare certain data or results as significant, to show a correlation, or to demonstrate a cause-effect relationship. It is easy to fall into the trap of bias. When we want to see something, we can usually find a way to make the data show it. I think the most critical takeaway of this article is the importance of looking at the evidence first before making up our minds with opinions.
I was surprised to learn in Robert Rubin’s article that climate change has previously and is still not completely considered a relevant variable when it comes to economic analysis. As Rubin says, the effort to reducing gas emissions and protecting the environment “is framed as a trade-off between environmental protection and economic prosperity…. [It] will impede economic growth, hurt business and hamper job creation.” However, perhaps rather than thinking of protecting the environment should be considered an investment for companies, rather than a trade-off or cost. Rubin makes a great point that our mentality is wrong. The choice we think we are making is inaccurate: “We do not face a choice between protecting our environment or protecting our economy. We face a choice between protecting our economy by protecting our environment.” Additionally, I thought Rubin’s explanation of the negative feedback loop was really interesting. There isn’t a linear correlation between economic production and environment damage, but a positive exponential correlation: “[A]s climate change continues, the damage…. will increase on an upward-sloping curve, that could become catastrophically steep, because of negative feedback loops and other factors.” This is really alarming because this suggests a snowball effect that could greatly hurt economic health. Finally, I think Rubin makes a great point when he says that “bad data leads to bad policy.” When it comes to statistics, it is so important to look for any lurking variable in the data. This is why I think Robert Rubin makes a great argument that climate change needs to be incorporated into our economic models.
Toggle Commented Feb 3, 2016 on ECON 102 at Jolly Green General
Like many other students have commented, I would have never thought of a negative interest rate policy as a possible solution to Japan’s deflation of the yen. Since falling prices can lead to lower profits, incomes, and eventually unemployment, it makes sense that the banks would want to stoke inflation with negative interest rates. In relation to our discussion of the circular-flow diagram, I can see why negative rates would encourage firms to borrow money for projects and investments. This might stimulate firms to increase production, which due to deflation has previously fallen. As a result, as we can see from the diagram, an increase in production within firms could lead to an increase in incomes and also an increase in demand within the market for goods and services. The logic of negative interest rates makes sense; however, like all policies, there are usually some negative side effects. If households are no longer receiving interest on their deposits but rather pay to keep their money in the financial market, I wonder if this would discourage households to keep their money in banks… Would households still have an incentive to keep their money in banks? While I don’t think the Japanese would suddenly be storing cash in their homes, perhaps they will buy government bonds instead or find another way to store their money. However, I guess that this would simply stimulate the standstill economy in another way. It will be interesting to see the cause-and-effect of Japan’s new financial policy.
Toggle Commented Jan 30, 2016 on ECON 102 at Jolly Green General
Taylor’s “Some Economics for Martin Luther King Jr. Day” makes some interesting ties between racial equality, economics, and mathematical models. In particular, I found Taylor’s third point interesting as it demonstrates the importance of creating useful, unbiased models, which can sometimes be a difficult task due to lurking variables. In both math and science classes, students are taught the importance of accounting for control variables. In order for two factors to be compared together, all other factors must be held constant. Otherwise, it would be difficult to determine any correlation between the two variables being studied. However, as Taylor points out, perhaps, while attempting to understand racial inequality and pay gay, we are choosing the wrong control variables or stratifying data incorrectly. Taylor explains that Glenn Lowry argues that “many of the observable factors are themselves the outcome of a history of discriminatory practices.” The differences in schooling, work experience, and family structure are “a consequence of the same structure of social relations” that led to discrimination in the first place. If this is true, then why is the data being stratified in terms of these factors? The models are misleading because of the way in which they were created. As a result, the models of the labor market were not demonstrating the reality of racial and economic discrimination. In a more general sense, this illustrates how important for us to think critically about what our models, which serve as a tool to simplify and analyze reality, are telling us and if these models are an accurate reflection of the world.
Toggle Commented Jan 23, 2016 on ECON 102 Reading at Jolly Green General
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Jan 22, 2016