Where are the teenager workers? An answer to The New York Times.

In a recent article published by the New York Times, Patricia Cohen and Ron Lieber made a brief inquiry on youth employment during summer 2015. In their writing piece, Cohen and Lieber open two windows for interpretation about factors affecting teenagers’ employment during summer school break. One of them is to believe that people between 16 and 19 years old are not interested in working at all, and instead they are doing “other stuff” (going to summer school, traveling or volunteering). The other window for interpretation is that the rivalry between teenagers and 20-years-older people for summer jobs has intensified in recent years. In their own words “Adults, desperate for second and third jobs to make ends meet, may be crowding out many teenagers”. The former rationale has to be ruled out from the analysis given that the BLS Household Survey barely allows for such an interpretation, which leads to only speculations. Otherwise, the latter issue about adults crowding out effect on teenagers may explain the picture better.

So, the argument goes the following way: youth summer employment is being taken by 20-years-and-older people. In other words, level of employment of 16-19-years-old gets affected by level of employment of 20-years-and-older people. If the American Economy creates certain number of jobs per month (average 221,000), those employments must be distributed among the population actively looking for jobs. Thus, variance in 20-years-and-older people must explain variance in youth employment. In addition, since the question is appropriately posed for summer jobs, the comparison must be run among comparable months of the year. Furthermore, given that gender plays a role in the number of hours worked by employees, and the hypothesis proposes 20-years-and-olders are chasing second jobs, it makes sense to look at 20-years-and-older women and men disjointedly.

Therefore, it also makes sense to regress 16-19-years-old’s level of employment on 20-years-and-older Women and Men’s level of employment for the months of January through June using BLS data from 2000 to 2015.

The results show that level of employment of teenagers get affected negatively by women level of employment. This effect can be interpreted as women competing fiercely against teenagers looking for a summer job. Data reveal that women tend to take jobs traditionally “meant” for teenagers. These results are twofold. First, data show that the crowding out effect maybe indeed happening. Second, data show that women might be the ones crowding out teenagers’ employment.

The situation exacerbates for young as the labor market reaches the summer. Generally speaking, women level employment affects teenagers’ less at the beginning of the year than by the summer. Coefficients in this regard show an increase from -0.58 in April to an estimated -0.75 in June. The meaning of the estimates is that teenagers have 75% less chances to get a job when women 20-years-and-older apply for it too in June. Thus, results on June data actually reinforce the hypothesis given that June and summer are supposed to have  jobs temporarily filled by teens.

The following table summarizes findings of regressions. Asterisk means 95% significance level.

Youth employment

Is Construction Investment Holding Back Job Creation?

Employment level statistics for the month of June 2015 looked a bit worrisome for some economists. At a glance, Construction was one of the missing sector in the list of industries significantly contributing to job creation. Indeed, Construction was the last sector in joining job creation after the Great Recession. Though ADP, the payroll company, reported that the sector added an estimated figure of 19,000 jobs during the month of June 2015 -which reflects a slight decline from the month of April-, establishment survey data from the U.S. Bureau of Labor Statistics (BLS) showed no addition for the Construction payroll data. More in detail, BLS employment data on Construction sector showed that it contracted at several specific specialties. The table below shows awful figures for a season which is said to be appropriate for outdoor works.
Employees on Construction Nonfarm Pay Roll
Specifically, activities that cut back in employment were nonresidential specialty trade contractors (-5.6K estimated employees), specialty trade contractor (-1.9K estimated employees), Residential Building (-6.1K estimated employees). Although there is much of a mix in the employment data for the sector, the aggregate figures suggest that a brief revision is worth doing in order to see whether there is an industry slow down, or just a deferred process due to weather conditions.

Well, the latest data on Construction put in place –May 2015- in the United States show no change in construction investment on month-to-month basis. Estimated change in construction spending for May 2015 was about 0.8% ($1,035.8 billion), with a margin error of +/- 1.5%. Furthermore, most of the estimated values do not support alternative hypothesis in order to reject the null hypothesis. In other words, there is no statistical evidence to claim that construction spending was different than zero (0) in the United States from April to May 2015. At the least, we could say that weather has not played a deferring factor for Construction activities, thereby affecting employment levels for June 2015.

Construction put in place Adjusted

Although data released by the U.S. Census Bureau is subject to constant revision, it seems unlikely that those figures change given the data on employment level. That is, employment levels data are sort of “confirming” that current investment in Construction is not enough for the sector to keep up with economic growth, at least for the summer season.

Employment statistics cannot be interpreted in a vacuum.

Employment statistics cannot be interpreted in a vacuum inasmuch as other economic indicators do determine employment growth. There are many nuances that require attention to detail. Indeed, details on June’s 2015 report on labor market are twofold. First, mining related industries –including utilities- started to adjust to low oil prices, as well as low demand for several manufacturing goods tempered high expectations risen before summer season. Likewise, spring low levels of investment on residential construction realized a decrease on employment for the summer. Second, Professional Business and Services continues to lead job creation in United States. In other words, oil prices do continue to affect the economy, though the industry started to adjust; strong dollar dragged international demand for U.S. metals products thereby affecting employment in manufacturing; third, low levels of investment in construction are taking a toll in employment creation.

Employment level June 2015.

Employment level June 2015.

Since Construction Investment slowed down in the spring, employment in the industry drops in the summer:

The latter factor should worry the most labor economist. Given that oil prices and exchange rates are beyond strictly control of United States institutions, and are also well known phenomena, investment in construction should call the attention of economic policy leaders. Since the beginning of the summer of 2015, when the statistics about GDP 2015Q1 were released, economists started to look at Investment in non-residential and residential structures. This sector is key for the seasonal employment since, as soon as weather allows for, construction and outdoor activities rebound. However, early in the spring 2015, this was not the case. Total residential construction put in place for the month of April 2015 decreased to $353,086 billion of dollars from 360,826 billion put in place the same month 2014, which equals 2 percent decrease over the year.

Residential Construction Put in Place, April 2015.

Residential Construction Put in Place, April 2015.

So, it should not surprise anyone that construction-contractors cut back employment as they see investment dropping. That very fact shows up in employment statistics astonishingly. Data from BLS show construction did not contribute significantly to augment employment levels nationally. Instead, 6.1KResidential construction building workers were dismiss from work; 5.6K Nonresidential specialty trade contractors were also cut from duty. That makes up to roughly 12K seasonal jobs that are crucial for year-round labor statistics.
These statistics are relevant for economics given that construction of new homes has many job spillovers in manufacturing industries. Another way to say the same is that whenever a new home is built, new sofas, TV’s, Kitchens, furniture, so on and so forth, are needed. Furthermore, the housing market was the sector that initiated the Great Recession, and construction as a sector was the latest in joining the path to recover. This issue helps to introduce the other weak flank of the current employment situation: manufacturing.

Manufacturing feels the spillover of strong dollar and low local demand:

The other drop in employment levels for June 2015 was seen in manufacturing, more precisely on metal related products which decreased employment level by 4.5K persons. In this case, apparently, it is not only internal demand which is cutting back employment levels, but also international demand for U.S. manufacture goods. In other words, last six months of strong dollar reduced the demand for U.S. manufacturing thereby affecting employment locally. Several sources have noted the extent to which the exchange rate is affecting negatively U.S. competitiveness and employment. Especially for metal products. Recent data on Current Account –Exports and Imports- released by the Bureau of Economic Analysis showed that during the first quarter of 2015 Goods exports decreased to $382.7 Billion from $409.1 billion. The drop in manufacture exports was mostly driven by a decrease in industrial supplies such as Petroleum, Chemicals and…. Metals products. This effect obviously spills over employment levels nationally. Once again, it is not a surprise.

Unemployment rates, June 2015.

Unemployment rates, June 2015.

The surprise:

Finally, what really happens to be a surprise is the revision of employment levels for the months of April and May 2015. The Bureau of Labor Statistics corrected its initial estimates on those figures by stating that April’s 2015 employments added were 187,000, and May’s employment added were 254,000. At first glance, April statistic fell below the threshold of 200,000 jobs per month, which should worry analysts to begin with. Then, when computed, the total amount of jobs not realized statistically amounts to 60,000. Thus, the monthly average for job gains is 221,000, which is slightly above the 200,000 threshold.

Average Figures on How Americans Spend Time 2003 – 2014.

The way Americans spend their time tends to drive their expending behavior. Either they may spend time working or spend time having fun. The latest release of the American Use Time Survey 2014 (ATUS) run by the U.S. Bureau of Labor Statistics (BLS) started to give more consistent data about changes on how Americans make use of their time. In its latest version which pertain 2014 data, the ATUS shows that Working and Work-Related are among the activities that had gone down since the Great Recession started. Nonetheless and although average of working hours levels are still below pre-Great Recession average, the Survey shows that those activities are rebounding at a good pace, which is consistent with data on labor market.


How do  Americans make use of their time?

ATUS data reveal that Leisure and Sport Activities have gone up, as well as Personal Care and Other Activities. The first year in which the BLS collected data for that survey, Americans spent in average 5.11 hours per day in Leisure and Sports related activities. After eleven years and one economic recession, Americans spend in average 5.30 hours per day doing the same things. Personal Care related activities where at an average of 9.34 hours per day before the Great Recession. However, since the beginning of the Great Recession, Americans spend in average almost half an hour more.


Time dedicated to Purchasing Goods and Services has also declined slightly. In average, Americans spend 44 minutes hours per day doing shopping, whereas in 2003 they spent roughly 48 minutes per day.


Interpreting these data happens to be a double edge sword.

Given that Average and Means are measures that get highly affected by outliers, analysts and readers must have caution while making inferences about these statistics. Furthermore, the perspective from where analysts operate tends to yield different conclusions. The first set of conclusions can be derived from the perspective of those that aim at interpreting the population as made up of Leisure-maximizing agents, whereas the second set of conclusion can be derived from the perspective of those who attempt to interpret the society as comprising of Income-maximizing agents. Therefore, some analysts may infer from these data that more time spent in Leisure activities might have a positive impact in quality life, personal health, and happiness. On the other hand, analysts could also conclude that Income could have been affected negatively and that population has become lazier.


Generalizing will always be risky:

As the reader may have notice, these data work out even for bolstering political and ideological statements. In spite of its ambiguity, ATUS data can be used for identifying major economic trends, and at the same time for depicting a bigger picture of the American culture, habits and, indeed, about the “American life”. Generalizing will always be risky, but when analysts clearly identify the boundaries of the data, and readers understand the limits of the sources, honest conclusion can be drawn from these rather obscure data.







Manufacturing industries hurry up toward Advanced Manufacturing.

By Catherine De Las Salas

By Catherine De Las Salas

Any time Economists learn facts about manufacturing industries, they conclude that the sector is contracting either at slower or faster pace. In fact, Economists focus too much on the speed of a long trend of economic specialization shared by developed countries. However, the news about manufacturing stem not from the speed of its own decline. Indeed, the focus on manufacturing should be on how fast or slow the sector transitions towards advanced manufacturing industries. Qualitative data released on June 25th 2015 give a hint on what to look at when surveying manufacturing companies. The following two statements unfold an important phase within manufacturing at which economist should be paying attention to:

  1. “Technology continues to improve our efficiency on the shop floor, equipment and machinery.” (Source).
  2. “We are turning to greater automation because of price pressures. 3D printers are becoming more powerful and less expensive. We will increase our use of that technology for our prototyping efforts.” (Source).

Those two comments were included in the Federal Reserve Bank of Kansas monthly survey on manufacturing released on June 25th 2015. These comments unveiled evidence about the “medium term” changes within the sector. Manufacturing industries hurry up toward improvements that allow them to compete efficiently against cheap labor overseas. Improvements in technology, new materials and new processes might be at the core of the sector’s concerns.

As the survey stands currently, it looks comprehensibly at production levels by measuring volume of shipments, volume of orders, and volume of inventories. The survey also works out well for unveiling employment levels by tracking the number of employees in factories as well as the average employee workweek. Insights on raw material prices and capital investments are detailed in every version of the survey. All of that measurement system is excellent and analytically useful. However, the indexes track no information about innovation of processes nor innovation of products within the sector. Perhaps, patents equipment replacement and investment in research and development may help economist understand not only the economic contraction of the sector, but also an eventual transition toward a stage of “advanced manufacturing”.

Data show consumers might be focused paying back debt.

Although news on Consumption Expenditures show a decrease in nondurable goods, that does not mean consumers are cutting back expenditure severely. Thus far –June 25th 2015-, economists believe the demand side of the economy affected economic growth in the first quarter of 2015. Data released on June 25th by the U.S. Bureau of Economic Analysis unveiled expenditures in nondurable goods dragged down personal consumption. Bear in mind that nondurable goods are mostly the set of products that consumers buy without using loans. This may indicate that consumers might be offsetting previous expenditure financed by loans. In other words, consumers might be paying back debt, as Durable goods also declined but did not so as sharply as nondurable did.


This very fact shows consumers spend responsible nowadays, which is promising for the months to come inasmuch as consumers balance their budgets. In spite of the actual decrease, the news are indeed positive in that regard. In fact, when comparing the same data on a year basis, Households experienced an increase in consumption expenditures of about 3.4% during the month of May 2015, when compared to the same month in 2014. Data also allow for some inferences about the role that interest rates are playing in both incentivizing and preventing consumption. If indeed, the data reveal that consumer spend nowadays responsible, monetary policy will find in that very fact a limit for its own policy purpose.


Consumption 2

On the other hand, the U.S. Bureau of Economic Analysis reported on June 25th that for the month of May, Personal Income increased 79 billion which equals 0.5% change from preceding month. Personal Disposable Income (DPI) also increased by the same percentage. Nominally speaking, Personal Consumption (PCE) expenditures increased $105.9 billion, or 0.9 percent. In April, personal income increased $69.6 billion, or 0.5 percent, DPI increased $57.0 billion, or 0.4 percent, and PCE increased $8.5 billion, or 0.1 percent, based on revised estimates.

What could you infer from 06/17/15 Federal Open Market Committee decision?

What can we infer from today’s Federal Open Market Committee decision?

Today’s Federal Open Market Committee (FOMC) decision corresponds to Fed’s previous statements about the current state of U.S. economy. First, data inputs on Capacity Utilization led timidly FOMC to insights on industry output gap. Second, the Beige Book clearly illuminated onto issues related to the economic geography of current economic conditions. Third, preliminary data on GDP 2015Q1 continued to be obviously a major concern. Finally, neither was employment at stake this time, nor inflation, nor household consumption. First, In spite of the Beige Book reveling regionally based concerns, they believe nothing can be fixed institutionally. The FOMC left unchanged interest rates for federal funds, which is the rate they use to influence market loan rates. Its statement of June 17th 2015 reads “To support continued progress toward maximum employment and price stability, the Committee today reaffirmed its view that the current 0 to 1/4 percent target range for the federal funds rate remains appropriate”.

On one hand, Oil Prices favor certain policy pressures mostly coming from Texas; therefore, policy preference coming from related industries such as transportation and utilities. On the other hand, other type of monetary policy preferences are coming from the most recent levels of exchange rates of U.S. dollar vis-à-vis Euro dollar. Here though, the FOMC has a muscle through influencing the rate. However, doubts are cast given the uneven reality of foreign exchange rates. Thus, not modifying the interest rate –in absents of the lowering option- seems the only way for the FOMC to bolster U.S. exports thereby doing so to employment. These two economic aspects made up the current concerns of Fed’s officials. Nonetheless, neither of them could be effectively influenced under the dual mandate of the FOMC. They demonstrated today liquidity trap keeps restraining monetary policy options.

What seems to be clear after today’s FOMC statement is that although the U.S. Federal Reserve aims at closing the output gap by influencing the interest rate, the institution has no clear diagnostic on Capacity Utilization. Apparently, Fed’s officials know data on Capacity Utilization no longer unveil facts worth concluding on output gap. What FOMC probably learned on Capacity Utilization during the second week of June is that Industrial Capacity on Manufacturing is below its long term average only 1.6 percent. The Federal Reserve Index for Manufacturing Industrial Capacity is at 77 percent. Non-durable goods Industrial Utilization Capacity is just 1.5 percent below its long term average. The latter Index showed 79.1 percent. Mining Industry Capacity Index shows the sector is adjusting to oil price rapidly and registered 83.3 percent Utilization.

Finally, trying to predict what the FOMC would do regarding the interest rate seems to be more complicated task than just plugging in policy targets on the Taylor Rule equation. Actually, the Taylor Rule is nothing but a crystal bowl inasmuch as economists look at it in isolation of surrounding data and information. Indeed, they seem to seriously consider broader sources of data and make a judgement comprehensively.

Preliminary Data on Services Industries during first quarter 2015.

The more data we know, the more facts we start to understand about the U.S. GDP contraction on the first quarter of 2015. The United States Census Bureau released on June 10th its preliminary data on the Services Sector Industries. Before adjusting by season and price changes, the data unveil unsurprisingly losses in Revenue for Utilities Industry, which comprises Gas and Electric distribution companies. The decrease for Gas related industrial activities was around 16% when compared to the same quarter in 2014. Likewise, Transportation would be hit with a decreases in revenue from Inland Water Transportation activities (3.4%); as well as Pipeline transportation activities (5%). The Utilities Industry as a whole would decrease its revenue in 6.1% in 2015Q1 compared to 2014Q1. Transportation and Warehousing increased revenue in 2.6%, though. An estimated of 551k employees work in the Utilities Industry.

The other losses in revenue would be seen in Newspaper publishing companies. Following the data, the activity continues to decline as Other Information Services activities soar. Newspaper publishing and related activities would drop its industry revenue by 3.8%. Otherwise, Other Information Services is said to have increased its revenue in 9.1% in the first quarter of 2015. Other Information Services comprises publishing activities like econometricus.com. Periodical publisher, Book Directory and Mailing list industries apparently declined by 6.1% and 2% respectively. Motion pictures and Sound Recording industry could have contracted its revenues by 2.4%, while Broadcasting (except internet) dropped by 0.6%. The activities on Specialized Design Services may have lost 6.6% in revenue during the first quarter of 2015.

The good news in Service Sector revenues will be apparently in the Education Services Industry, which will show, if confirmed, increases near 10.4% in 2015Q1. Administrative Support Businesses is also said to have had one of the best economic performance with an alleged increase in Revenue of roughly 6.8% when comparing 2015Q1 vis-à-vis 2014Q1. In the third place of revenue positive variation would be Real Estate which increased 5.7%, closely followed by Professional, Scientific, and Technical Services that did so by 5.6%. Accommodation Industry, also preliminary, showed an increase of 5.6%. Health Care percent change in revenue is estimated to be around 3.1.


“Survey Description”:

“The U.S. Census Bureau conducts the Quarterly Services Survey (QSS) to provide national estimates of quarterly revenue for employer firms located in the United States and classified in select service industries. The current total sample size is approximately 19,000 employer firms” (U.S. Census Bureau).

Is the Current U.S. Dollar Strong All Over the World?

The “Strong Dollar” factor:

“Strong Dollar” is said to be one of the main causes explaining the poor economic performance of the United States during the first quarter of 2015. United States’ exports were affected by the appreciation of the currency vis-à-vis some of the foreign currencies. Likewise, exports towards the United States benefited from the U.S. Dollar appreciation. In aggregated terms, currencies of major U.S. trade partners, versus the U.S. dollar, have gone up in average by roughly 3.2% in the last five months of 2015. This trend can be seen in the picture below on blue line (1 Broad). Furthermore, a subset of other major currencies that circulate worldwide have appreciated since January by an average of 5.7% against the U.S. dollar, which can be observed in the orange line in the graph below (2 Major Currencies). The euro, instead, has depreciated 8.3% since the beginning of the year (Yellow line in the graph below). There is where the competitive advantage resides for Europe nowadays.


Who’s to blame?

When it comes to blame foreign trade for poor economic performance in US, Asian countries come to mind of Americans. For economic growth on 2015Q1, such a statement seems to be somewhat ambiguous. The graph below shows how major Asian currencies have performed recently. The Yuan, dotted white line in the graph, has been mostly steady for what has bygone of 2015. Otherwise, the currency that has depreciated the most, amongst Asians monetary markets, is the Taiwanese Dollar. The Indian Rupee initiated the year with a downward trending which lasted until the second week of April; then, the Rupee started to gain value against the U.S. Dollar. South Korean currency, the Won, had its lowest value against U.S. Dollar this year by the last week of April. The Won did so after having been depreciating since the first week of March. Dollar from Singapore has also been depreciating since early March after a spike in its value against dollar (Yellow line in the graph).

Currency 2
In order to elaborate these currency series, we took the value of the currency against the U.S. Dollar at its value during the first week of 2015, and use such value as index. The data source is the Board of Governors of the Federal Reserve System, which aggregates the currency data for major U.S. trading partners. The Federal Reserve defines these aggregated data as follows:
1) Broad: “A weighted average of the foreign exchange value of the U.S. dollar against the currencies of a broad group of major U.S. trading partners”.
2) Major Currency: “A weighted average of the foreign exchange value of the U.S. dollar against a subset of the broad index currencies that circulate widely outside the country of issue”.
3) OITP: “A weighted average of the foreign exchange value of the U.S. dollar against a subset of the broad index currencies that do not circulate widely outside the country of issue.