Upon looking at a Macro indicator like Retail sales in a given economy it may provide very important data that can be used by decision makers to direct policy or make general business decisions. In order to understand this data it is important to understand the difference between a direct signal and an indirect signal. These two items if used properly will allow a decision maker the correctly direct their efforts.

First starting with direct signals. These signals can be defined as a database of facts that are not up for debate. These signals measure exactly what you want them to measure and provide a database of information. For Example looking at Retail Sales. If a decision maker in a retail segment of the economy is looking to see where retail sales are over the period of January-­‐May, they would look to the retail sales data. Whatever it shows is what retails sales are, this is not data that is up for debate, either sales are up or sales are down and the point at either end is where they are. However, an indirect signal is a signal that leaves some level of interpretation. These signals are indicators from one part of the economy that can help draw conclusions to another part. For Example, keeping with retail sales. A decision maker in the manufacturing of goods that are sold in retail sales sees that retail sales have had a steady increase over the past 6 months; they might infer that they want to increase production of goods due to the increased purchasing of retail items. Although this might be the decision made by the manufacturer, it is not a guarantee that his sales will increase. Although the decision to increase production is based on increased

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purchases of retail goods seems logical, it is possible that it will not work 100% of the time. It is possible that there is a correlation between these two segments of the economy, but unfortunately it is not always 100% guarantee that they will move together.

Looking at the same category of Retail Sales over a period of time there are a multitude of direct and indirect signals associated with this category depending on what segment of the economy a business is based in. As stated in the previous example, if a manufacturer of retail goods sees that over that time period sales have steadily increased, then it might stand to reason that increasing production would make sense. However if sales appear to have spiked in one period and remain relatively constant throughout the rest, then it might stand to reason that the one spike was an outlier event and that production should remain constant. This is one example of an indirect signal associated to the category of Retail Sales.

Looking at the same category of Retail Sales, a retail sales business can look at the same data and infer that if sales have steadily increased over the period that an increase in inventory should take place to account for the increased purchasing. This would be an example of a direct signal. The information in Retail Sales as it pertains to a Retail Sales decision maker, this most basic direct signal is just that, what the retail sales are doing over a given period or at a given point.

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Lastly looking at a segment of the economy outside of retail sales and manufacturing of retail goods, lets look at say the travel sales (i.e. Travel Agency, Airline Tickets, etc..). These sales are slightly higher priced that typical retail sales, but someone working in these segments of the economy might look at an increase in retail sales to show that people are spending more money and that sales to this segment could increase in the coming months due to people spending more money. This is not a guarantee that it will happen but a decision maker in this sector can make the inference that it will.

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Looking at the situation in Bahrain; it was decided that Bahraini households would be given BD50 ($133) monthly to make the purchasing of food and other necessities easier. This decision excludes non-­‐Bahraini residents, which make up 52.7% of the entire population. We must look to the description of Cost-­‐Benefit Analysis put forth by Henry Hazlitt to better understand the implications of such a policy. Hazlitt states, “The art of economics consists in looking not merely at the immediate but at the longer effects of any act or policy; it consists in tracing the consequences of that policy not merely for one group by for all groups…”

What Hazlitt is saying by this is that when a policy or act is being considered, it must not only look at those who will directly benefit from this act, but who also might benefit or be “hurt” by the action, both in the short term and long term. In a simple example; Lowering Interest rates can be seen as a positive act for those who want access to “cheaper” money, however if you look at a different group of people who are trying to accumulate wealth through higher interest rates, it severely “hurts” them. Examples of people “hurt” by this action are individuals in retirement or approaching retirement. This group depends on the interest rate to either prolong their savings or to accrue the interest in order to retire. So by helping those who want access to cheaper money, it also has ill effects on those accruing wealth through higher interest rates. Looking back to the policy enacted in Bahrain, the increased money for Bahraini residents can be seen as a very positive thing. However since they only make up a 4

minority share of the overall population, it can be seen as “hurting” the remaining 52% of the non-­‐residents. The key issue is that the value of the dollar on the international market caused by inflation is much weaker. (This inflation could have been caused by too much currency being circulated in the market). With inflation comes a

rise in prices. The same $1 item will not be able to be purchased with $1 anymore.

This policy, although it is aiding a small segment of the population, is not beneficial for all. The large numbers of non-­‐residents are still being ill affected by the rising prices due to inflation. With all the aid being targeted at one group, it could over time affect the distribution of wealth and buying power/demand of goods of those not being aided by the BD50. The intent of the aid, to residents, is to make the purchase of everyday goods such as food easier. However if all member of the population are not being provided with aid or stabilized pricing eventually those outside the aid can develop lowered levels of ability to purchase goods and eventually lowered demand of those goods, depending on the length/level of inflation and ensuing price increases. If this continues over a long period of time, the ramifications could be disastrous. Looking at it through a very severe scope, over a long period of time, if individuals not being aided by the policy start to lose buying power, they may not only seek their goods outside of the market, but could potentially seek residence elsewhere. If this large segment of the population begins to emigrate Bahrain the overall economy could plummet due to a decreased labor force. Which could in turn decrease overall production in Bahrain.

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The overall policy although seemingly useful to a segment of the population, looking at it through Hazlitt’s lesson, could have very negative affects on the overall population; up to and possibly including a decrease in labor force and decrease in overall production. Just like most things in economics these are not guarantees, but potential outcomes based off of historical data and theory.

Part A) Looking at Tables A and B it is important to note a few items. Starting in Table A looking at the unemployment rate, it seems to be holding right around 6%. The Labor force has seen some fluctuation, but none of substantial change. There has been a very slight negative change in job losers entering the unemployment sector. Looking at the duration of unemployment; Unemployment lasting longer that 27 weeks has fallen compared to June ’14. This leads me to believe that although unemployment is still an issue, the duration of job seekers out of work long term is falling.

Shifting to the Table B employment in Durable Goods, which was growing between June and July has suddenly slowed growth significantly. This could be due to the warm months coming to an end where items such as Air Conditioners, New Cars and other large ticket items is slowing down and thus less jobs are available in those sectors. An item that was interesting was a sudden decrease in employment in the non-­‐durable sector. Over July and August we see both months have negative employment growth. This means there are people losing jobs in those sectors. It could be due to seasonal employment ending at many retail establishments. It will

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be interesting to see if there is a spike in October and November in this sector due to a large purchasing season around the holidays.

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Part B) Looking at Table A-­‐2 and at figures for teenager vs over 20 unemployment, we see that the unemployment rate in teenagers grew during the summer months while over 20 unemployment rates remained fairly constant. This is interesting because I would expect unemployment rates in teenagers to drop in the summer and rise as fall hits due to people going back to school. However we see the opposite of that leading me the think that there were less jobs available for teens with the limited education level. This assumption holds that the labor force of teenagers does not change as they return to school and become not listed as part of the unemployment numbers. The unemployment rates for Whites, Blacks, Latinos and Asians are as follows:

Race White Black Asian Latino

Unemployment Rate 5-­‐5.5% 11-­‐12% 4-­‐5% 7-­‐8%

We see that the Black population has the largest unemployment rate by far and that the Asian and White population are close to each other. However if you look at the unemployment rate as a figure of the overall population of each category we see that labor forces Asians is considerably smaller than any other population and that the Hispanic and Black labor forces are similar where as the White labor force is considerably higher than any other category. A 5% unemployment rate in White 8

population is considerably higher than a 5% unemployment rate in the Asian population. Part C) Looking at the different levels of education we see for the most part what would be expected in the economy today. Those with less education are more likely to be unemployed. The unemployment rate for those with less than a high school diploma is around 9% and for those with bachelors or higher is only around 3%. With higher unemployment rates overall in the market, people are looking for more qualified individuals with more education. This can be seen as a way to cut back on time required to train someone. If they have a higher education, it might take less time to train that person than someone with lesser education. Overall this could mean faster turn times to becoming a productive employee if you have a higher education.

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Part D) In august of 2014 it is reported that there are 2,224,000 farmers, which is roughly 1.5% of the employed population. Looking at people in the part-­‐time sector and looking at the table below with data taken from A-­‐8, it appears that the majority of people working part-­‐time is due to non-­‐economic reasons. Some of the reasons might be school, childcare problems, and personal obligations. It is tough to say if these reasons are want or required. The next largest sector of part-­‐time workers is for Economic reasons meaning that there was either slack work or that is all they could find. This sector does not have a choice to only work part time.

Reason For Part Time Work # Employed in Part-­‐ Time Work (in Thousands) 7,277 4,261 2,587 19,526 % of total part time work 21.6% 12.7% 7.7% 58%

Economic Reasons E Slack Work Could Only Find Part-­‐Time Non-­‐Economic Reasons

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Part E) I would make the argument that method U-­‐4 is the best method for computing labor underutilization. This method take the official unemployment rate, but also attached discouraged workers and adds them into the equation. However, I would like to see one more portion added to this computation method. It would be interesting to see that same number plus those working part-­‐time for economic reasons. These are individuals who are seeking full-­‐time employment but are not able to attain it. I find the figure of people who are marginally attached to the labor force (not currently working or looking), unimportant. These people would not be considered unemployed by the definition of unemployed and thus are not important in looking at how labor is being under utilized.

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