Friday, July 14, 2017

Marginally Attached Workers in New Zealand

Discouraged workers are those who have actively searched for jobs in the past 12 months but believe that there are no jobs for them. OECD publishes data on what they call marginally attached workers. They are defined Marginally attached are persons aged 15 and over, neither employed, nor actively looking for work, but are willing/desire to work and are available for taking a job during the survey reference week. Additionally, when this applies, they have looked for work during the past 12 months. This measure is broader in scope than the discouraged worker data-set and may be used to produce alternative measures of labor underutilization.” 

The figure below plots New Zealand, Australia (shorter sample), and the United States OECD data as a percent of working age population (15-64) from 2000. New Zealand and Australia are on the primary axis and the U.S. is on the secondary axis. The picture is rather dramatic and alarming. The trend is rising in New Zealand and falling in Australia and the United States. We have nearly 300,000 marginally attached workers in New Zealand. Given the relatively smaller size of New Zealand labor market, that amount to more than 10 percent of the working age population. The number of workers in the U.S. is really a small relative to the size of the working age population. On average, Australia’s rate of marginally attached workers is more than 10 times as large as that of the U.S. New Zealand’s is more than three times as large as Australia’s.[1]

These workers could have been unemployed for a long time; or do not have the updated skills needed to get a job; or have suffered from sort of discrimination. These people would take a job if it were offered. Usually the number of such workers falls during the recovery as in the case of the U.S. and Australia in the figure below. Surprisingly, the number increased in New Zealand. Discouraged workers do not include those who have dropped out of the labor force because they went back to school, disables, and women who are on maternity leave.

New Zealand's labor statistics appear healthy, except for this strange statistic. The upward trend is alarming because there might be thousands of highly skilled and productive workers who are discounted for other reasons. I did not find any papers on the subject in New Zealand Ministry of Business, Innovation, and Employment.













razzakw@gmail.com 


[1] New Zealand sample is 2000-2014, Australia and the U.S. 2007-2014.

Sunday, July 2, 2017

The Missing Productivity Conundrum

Why has productivity been falling everywhere?

The latest issue of the Journal of Economic Perspectives has two papers on this problem.[1]The first is by Martin Feldstein, who focuses on the mismeasurement of real GDP, hence the mismeasurement hypothesis.[2] He says, “After studying the methods used by the US government statistical agencies as well as the extensive previous academic literature on this subject, I have concluded that, despite the various improvements to statistical methods that have been made through the years, the official data understate the changes of real output and productivity.” He emphasizes the inability to measure the “improvements in the quality of goods and services,” and especially for new goods and services.  

The second paper disputes the mismeasurement hypothesis.[3] Chad Syverson focuses on ICT. He shows evidence that the slowdown in productivity has occurred in many countries and not only in the U.S. and perhaps long before 2004. (See (Haldane) for the same in the U.K.) He also shows that the surplus created by the new goods and services (i.e., ICT) is far less than the missing output, which caused the slowdown in productivity. He also makes other points worth examining.

My argument is that mismeasurement explains a lot of the missing productivity in OECD countries.

First, labor productivity, measured by the ratio output/input, is pertinent to profit-maximizing firms. It makes no sense to talk about productivity, and to invest in non-profit maximizing firms and sectors.  

Second, GDP data include both profit-maximizing firms (and sectors) output and non-profit maximizing public sectors and government agencies’ output. Inability to measure the quality of goods and services notwithstanding, services output in particular is very difficult to measure, especially in non-profit maximizing sectors. Imagine the difficulty of measuring output in the public sector and government administration and services. It might be easier to measure the output of a private school or a private hospital services by inferring output from the profit function. The data, however, do not allow for such classification. Therefore, I argue that aggregate output (total real GDP) is not the right measure to use for calculating labor productivity because it includes a lot of “hard to measure outputs.”  

Third, the higher the share of services in GDP the lower measured labor productivity.

To illustrate, for New Zealand, I measure labor productivity using the sectoral data ANZSIC06 published by Stat NZ and employment by sectors (data for hours by industry are unavailable). The data are available from 2004 to 2017. Then I modify this labor productivity by subtracting the following “services” sectors data from total industry output and employment: Professional, Scientific, Technical, Administrative and Support Services, Public Administration and Safety, Education and Training, Health Care and Social Assistance, Arts, Recreation and Other Services, rental and real estate activity, and a column labeled “Not Specified.” I did not remove: Financial and Insurance Services because I think that this sector’s output could be measured or inferred from the firm’s profit function.[4]

I convert the two productivity measures to indexes (2004=100). Here is the plot.



It is clear that labor productivity (less services) is significantly higher than the conventional measure which includes public sector services.

Caveat: there must be a number of firms and agencies within the services sectors, which I removed, that are profit-maximizing. For example, in the public service sectors there are private schools, private hospitals, private arts and recreation etc. I cannot separate these from the data because I do not have enough information.

The average share of these services in GDP over the sample is 52 percent. It has been relatively stable.

This graph plots the growth rate of NZ labor productivity.




New Zealand missing growth is nearly 1 percentage point on average, which is quite a significant mismeasurement.

Labor productivity will continue to be understated until measurements of services are addressed by statistical agencies.  


razzakw@gmail.com


[1] Journal of Economic Perspectives Vol. 31, Issue 2, Spring 2017.
[2] Underestimating the Real Growth of GDP, Personal Income, and Productivity.
[3] Challenges to Mismeasurement Explanations for the US Productivity Slowdown.
[4] The Conference Board data KLEMS report figures for they call Market Activity whereby these sectors are subtracted from the total industry data.

Friday, May 12, 2017

The evidence-based New Zealand housing price policies

Last week I reported some estimates of the long-run magnitudes of the effects of demand and supply measures on the New Zealand house price index. The question is what to do with this evidence.
It seems obvious from the data that the most effective way to dampen the house price increase is to increase the supply of housing.

Demand management is less effective and could be even damaging. It is rather silly to argue that a recession, caused by tight monetary policy (i.e., higher interest rate) or contractionary fiscal policy (i.e., new taxes), is needed to reduce housing prices and resolve the affordability problem.

Specific taxes may reduce speculative excesses. The Treasury knows all about the size, the efficacy, etc. but this is an election year and politicians would be reluctant to introduce new taxes.

Higher real house prices (i.e., adjusted for inflation) imply higher wealth for Kiwis. Wealth is not a bad thing, or is it? Recall that the main concerns about high house prices are about affordability and financial instability. Just as many Kiwis will benefit from having affordable housing many middle class Kiwis will lose from lower housing prices. Policy errors could send the whole economy into a deep recession because most of the assets held by New Zealanders are housing’s.

Also on the demand management side, restricting immigration has a small effect on housing prices as the data show, unless we have a huge reduction or shutting down the immigration program completely. In addition to immigration, there could be corporations, banks, or even nonresidents in additional to people buying houses in New Zealand. 

The price and the quantity (the number) of housing are determined (simultaneously) by the intersection of demand and supply. These curves shift up and down because of shocks. In absence of interventions, restrictions and regulations both the price and the quantity adjust until they settle at a new equilibrium.

That is not the case in reality. We have two independent regulations affecting the quantity and the price of housing.

First, we know that there have been increasing building regulations, requirements, and land restrictions among other regulations that affect the quantity of housing. These regulations (interventions) increased the cost, and essentially altered the slope of the supply curve of housing. When the demand for housing increases because of the increase in income, population, immigration etc. most of the adjustment to the shock, under such regulations, has to be in the price, naturally, because the quantity is restricted by regulations. Thus, more demand means higher prices.

Second, the RBNZ intervenes with different regulations to deal with the house price increase under the new, widely followed, international arrangements of maintaining financial stability.[1]  Central banks regulate credit flow. They essentially try to manage demand for housing.  However, the problem is initially on the supply side really.

So what we have is two different regulators regulating the price and the quantity in the housing market, independently and fully discretionary, making it impossible for prices and quantities to adjust to shocks. The natural mechanism of adjustment in the housing market is impaired and it has no chance of working under these sorts of regulations.

To resolve the housing problem we have to allow the quantity of housing to vary by increasing the supply of housing (i.e., relaxing restrictions on the quantity of housing). This will bring the housing price down. One hundred thousand new building consents reduce the price house index by about 7000 index points. However, we should also allow the price of housing to vary (i.e., by relaxing the restrictions on credit and the banking system). Otherwise, we will continue to have adjustment problems in the housing market.

New Zealand banking system is good by international standards. Credit rating is Aaa. The global financial crisis did not affect us because the banking standards are high. Banks know best how to lend, to whom, and at what price, under the RBNZ’s banking supervision guidelines. These guidelines have been in place for some time; they are well tested. Therefore, to bring the housing market back to normal by removing restrictions on the supply side, discretionary intervention in the credit market needs reexamination.


razzakw@gmail.co 

[1] Macro-prudential policy is a discretionary regulatory intervention aims, in this case, at restricting credit in housing market when the central bank thinks there are “bubbles” or “speculative excesses” in order to prevent “systemic risk” and financial instability. Read Lars P. Hansen “Challenges in identifying and measuring systemic risk,” CEMFI working paper No. 1305 www.cemfi.es. I have written about this before (see older blogs) and I still believe that it is quite murky area in economic policy. 

Sunday, April 30, 2017

New Zealand House Price, Bubbles and Immigration

Many people seem to link high housing prices with bubbles and immigration. This is an election year so more will be said as the date of the election draws closer. Unfortunately, I have not seen any economic analysis and measurements except from some graphs and some stories, here and there.

I think that bivariate graphs are fine, but uninformative of a multivariate problem like this one. It is quite common to eyeball a strong graphical correlation, which disappears in regression analysis. Some stories, however, are reasonable. For example, expansionary (i.e., loose) monetary policy usually results in credit expansion, which leads to a higher demand for housing, and higher prices. I showed in a blog before that excess supply of money is also correlated with higher housing prices at a reasonable lag. Some dismiss money and talk about low interest rate instead. Fine too, because a lower interest rate increases the demand for money and credit and leads to higher asset prices. There is a general agreement that looser monetary policy also stimulates output (GDP) in the short run. It ends up opening a positive output gap whereby GDP exceeds its long-run potential over the business cycle. That must have an effect on the demand for housing, hence high housing price. These stories are fairly grounded in economic theory.

 Housing supply issues are also widely acknowledged. Finally, the story that an increase in immigration could add a demand pressure on housing, why not? But where is the test? The graph shows cyclical variations in the housing price index and net immigration. There is a weak correlation (0.30), where immigration leads, but totally breaks down in 2008.


Bubbles mean that the increase in housing prices is not justified by the economic fundamentals. I think that there is no reliable statistical test for bubbles and I have not seen a credible and convincing proof for bubbles. However, when the supply of housing is fixed for whatever reason then shocks that shift up the demand for housing (imagine a downward slopping curve intersecting the vertical supply curve) will only result in ever higher housing prices. This is quite easy to understand. 

Here are some simple measurements. I estimate a simple equation for housing prices in New Zealand, whereby the level of the house price index (base=1000) depends on aggregate income (GDP), which reflects money and credit markets, interest rate, fiscal policy factors….etc. (think about the goods and money markets).[1] It also depends on a measure of the supply of housings, which I approximate by the ratio of the value of new building consents / the value of the existing stock of housing. Finally, we have net immigration as an addition explanatory.[2]

Looking at the estimated long-run equilibrium of the model and the actual housing price index shows no bubbles whatsoever. The housing price fluctuates around the equilibrium closely. It was above equilibrium from 1996 to 2000; slightly overshot its equilibrium value in 2015; and less than or equal to equilibrium during the rest of the period.



The coefficient of net immigration, conditional on demand and supply factors, is 0.015 (with a standard deviation of 0.0055). So an increase (decrease) of 50,000 people leads to an increase (decrease) in the housing price index by 750 points, e.g., from 1000 to 1750. That is a growth of 75 percent. GDP has a larger effect on housing prices. The coefficients is 0.059 (with standard error 0.0050). The supply factors have a coefficient of -0.07 (standard error 0.0550). An increase in new building consents relative to the stock of housing lowers the housing price index. This is a very large coefficient. An increase of 100,000 new building consents lowers the housing price index by 7000 points.  

Unfortunately I do not have data for Auckland and other regional housing markets so my analysis is restricted to New Zealand as a whole. I hope that this is a useful analysis. Someone may want to take it further, which could shed more light on the matter. Panel data analysis could be done if regional data are available. 


[1] We cannot have credit in the model because it is highly correlated with GDP. The same is true for money.

[2] The equation is estimated over the period Mar 1996 to Dec 2016 using two-sided Dynamic-OLS (Phillips-Loreatn, 1991). This is a most efficient estimator. It is equivalent to a system of equations and accounts for endogeneity and serial correlation. Housing price index is regressed on a constant term and the levels of GDP, the ratio of new building consents / housing stock ratio, and net immigration; the growth rates of these three variables; one lag and one lead of the growth rates (i.e. the two-sidedness); and an error correction term. It assumes that the levels are integrated of order 1, and cointegrated. Standard errors are consistent Newey-West. The data are from the RBNZ website. Monthly new building consents are from Stat NZ. It includes residential buildings, houses, apartments, townhouses, and retirement village units. I ignored public building and constructions.     


Friday, January 20, 2017

The U.S. Presidents and the Economy?

The U.S. has a new president. Hopes are for a better economy. The U.S. presidents could affect the lives of millions, some for better and some for worse. The question is how do they affect the average. The affect the macro-economy primarily via their tax policies because taxes, whether on labor income or capital, affect productivity, labor supply and capital accumulation. Most economists agree that taxes have real effects. Other policies such as the spending on infrastructure, defense, the environment, health, education, R&D and social policies can also have some effect on growth and income per capita. However, there is no consensus about the empirical size of the average effects of these policies. The president's policy effects on growth may take a much longer time than the time he spends in office. These policies also change, and expected to change, from one president to another. A tax reduction today may well mean a tax increase tomorrow.  

Here are the average growth rates of real GDP and real GDP per capita for the periods of the presidencies of Carter, Reagan, Bush I, Clinton, Bush II, and Obama. GDP may not be a perfect measure of well being, but that is the only measure available today. These growth rates did not vary across presidents significantly, except for the Obama presidency. For him, the growth rates are relatively lower than the rest and lower than the overall averages from 1977 to 2015. However, the Obama presidency coincided with the global financial crisis and the Great Recession from October 2007 to April 2009. The U.S. economy also experienced recessions during Bush I and Bush II presidencies. For Bush I, there was a recession from October 1989 to January 1991. For Bush II, there was a short recession from January 2001 to July 2001. In these three presidencies, the growth rates were relatively lower. However, there is no evidence that presidents Bush I, II, and Obama caused these recessions just as there is no evidence that Carter, Reagan, and Clinton caused the expansions.The people were equally better off during the Reagan and Clinton eras even though they are two different presidents with very different policies. 


Average of Annual Real GDP and Real GDP per Capita Growth Rates (%)

GDP
GDP per Capita
Std.
Carter
1977-1981
3.2
2.2
2.5
Reagan
1981-1989
3.5
2.6
2.6
Bush I
1989-1993
2.3
1.1
1.8
Clinton
1993-2001
3.9
2.6
0.8
Bush II
2001-2009
2.1
1.2
1.3
Obama*
2009-2016
1.5
0.4
1.9
Std. is the standard deviation. These are almost the same for both growth rates.
Asterisk: data are up to2015.
Red color denotes growth below the overall average and periods included recessions.
The data source is the Federal Reserve Bank of St. Louis. 




Wednesday, January 18, 2017

Iraq: education from 3000 B.C. to date

A few weeks ago I showed that Iraq has not published data on education since 2003. The wars, the UN sanctions, and lastly the invasion in 2003 had adversely affected education. Historically, Iraq has been the cradle of civilization and its history is associated with a lot of human capital. In this blog I retell the stories of the Sumerian education system since 3000 B.C. from Kramer (1956) classic work. Unlike Iraq today, their ancestors, the Sumerians,  recorded everything.

In "History Begins At Sumer," Samuel Kramer (1956) talks about the discovery of the first ever written document in the world. It was found in Erech in Southern Iraq. It included more than a thousand small tablets inscribed with economics and administrative memos. The Sumerian invention of the Cuneiform system of writing led to the establishment of he first school in the history of mankind. Some of the tablets were designed for study and practice. That suggest that 3000 B.C. Sumerians thought about teaching and learning. In 1902-1903 a considerable number of school textbooks were dug out in ancient Shuruppak the home city of the Sumerian Noah. These textbooks dated from about 2500 B.C.


The school system in Sumer flourished in the last half of the third millennium. Thousands of tablets were excavated. There were junior and high scribes, royal and temple scrips, some were administrative and others became high government officials.

During the first half of the second millennium, hundreds of practice tablets, which contained exercises prepared by the students as part of the daily schoolwork. Some were scratches of first-graders while others were written by graduates. Tablets written by the teachers were also excavated, which have information about school life, objectives, curriculum and teaching methods.

The objective of the Sumerian school system was to train scribes whose writing skills were needed to maintain the administrative and economic systems in the land. Some graduates would serve the palace while others would work at the temple. Over time, the schools progressed to become the center of culture in Sumer. Scientists who studies theology, botanical, zoological, geographical, mathematical, grammatical, and linguistic. Schools were also centers for creative writing. Although schools served the temple and the palace primarily, they became more secular over time. The curriculum became more secular.

The tablets also indicate that education was neither compulsory nor universal. Students pay tuition fees, which cover the salaries of the teachers.  In 1946 a German Cuneiformist Nikolaus Schneider proved that only the rich were able to send their kids to school.  He compiled a list of the names of five hundred students and the occupations of their fathers. The information was taken from thousands of tablets. The tablets also reveal that only males were listed as scribes. The head of the school was called the school father. The assistant professor was called the big brother whose duties include preparing the tablets for the students and hear them recite the material from memory. Other faculty were the man in charge of drawing, the an in charge of services, and the man in charge of the whip. Obviously meant the man responsible for disciplining the students. There were caning and punishments. 

There is a large amount of information about the schools curriculum. The actual work of the students are found. The work includes tablets written by beginners and others written by advanced students. The differences were clear. The work of advanced students is indistinguishable from the work of the professors.  The curriculum covers two groups: a semi scientific and scholarly and the literary and creative. The first was developed out of the school's objective, which was to teach the students the writing of the language. They classified the Sumerian language into groups in related word and phrases and had the students to memorize them, and copy them until they could reproduce them. Textbooks are found. They became complete in the third millennium B.C. and they got standardized allover the Sumerian schools. They included names of trees and reeds, animals including birds and insects, cities, towns, and villages, and stones and minerals. The way the material was compiled is consistent with botanical, zoology, geographical, and mineralogical grouping. Tablets of various mathematical problems were also found in large numbers. Other tablets contained linguistic and grammatical problems. Some were inscribed with long lists of complexes and verbal forms.Most interestingly, the Sumerians developed the first ever dictionary. That was a result of the conquest by the Semitic Akkadians in the last quarter of the third millennium. The Akkadians borrowed the Sumerian script and studied and imitated the literary work long after the Sumerian language became extinct as a spoken language.  

Kramer says that hundreds of tablets of literary work were written in the forms of poems from as long as 50 lines to a 1000 lines. The excavated material included myths and epics in the forms of narrative poems about gods and heroes; hymns of gods and kings; and passionate expressions of sorrow and sadness for the destruction of Sumerian cities. They also included wisdom compositions, which included proverbs, fables, and essays. A large number of the tables were the work of students.

In summary, Mesopotamia, which is the modern day Iraq, was indeed the birthplace of education and schooling, among other things. Kramer recorded thirty nine "first" cases in history found in Sumer 5000 years ago. The process of creating and accumulating knowledge has been interrupted repeatedly through out the history of the region and for different reasons. The Mongols destroyed everything in Iraq in 1258, but Iraq rose again. The history of Iraq is long; it is not the end of history yet. 


    

Wednesday, December 28, 2016

The post 2003 Iraqi economy in numbers (part ten)


The distance from the frontier

Halfway

The new statistics the World Bank like to publish are indicative of the progress of the free market.
One widely publicized statistic is the distance from the frontier . It measures the distance of a certain economy to the frontier, which represents the best performance observed on each of the indicators across all economies. An economy's distance to the frontier from zero to 100, where 0 represents the lowest performance and a 100 represents the frontier. For example, a score of 75 in 2016 means an economy is 25 points away from the frontier constructed from the best performances across all economies and across time. A score of 80 in 2017 would indicate the economy has improved. 

Iraq's score post-2003 is somewhere between 45 and 50 on average. So Iraq is halfway from 100. It is better than Iran, but worse than almost all Arab countries such as Bahrain, Kuwait, Oman, Jordan etc. In the table below are World Bank statistics about time needed to start and run a business. It takes a year to build a warehouse, two years to enforce a contract, and two months to get electricity...etc. One could register a business and be ready to work in one or two days in advanced Western economies, This would give you an idea about the state of the market in Iraq. Iraq is not good for business 13 years after the system has changed.



Doing Business Statistics

Post 2003
Time required to build a warehouse (days)
224
Time required to enforce a contract (days)
520
Time required to get electricity (days)
58
Time required to obtain an operating license (days)
19.4
Time required to register property (days)
51
Time required to start a business (days)
30.3
Source: World Bank



 ممارسة أنشطة الاعمال 

منتصف الطريق

يقوم البنك الدولي بنشر مؤشرات حول التقدم الذي يجري تجاه تعميق كفاءة اقتصاديات السوق المفتوح. ويسمى التقرير "ممارسة أنشطة الاعمال) ويمكنني ترجمة المؤشر الذي يبلور مجموعة من المؤشرات "بالمسافة من الريادة" أو "المسافة من المقدمة" اذا صح التعريب. ويعني ان هناك دول في المقدمة واخرى في المؤخرة ودول عديدة فيما بينهما. والمسافة تقاس على معيار بين 0 و100 حيث ان 100 تمثل احسن اداء وفي الريادة و 0 في المؤخرة. فعلى سبيل المثال، اذا كان الرقم 75 غي سنة 2016 فهذا يعني ان هذا الاقتصاد يبعد 25 نقطة من الريادة.

حصل العراق على متوسط مقداره 45 الى 50 في السنوات بعد 2003. وبما انه بعيد عن 100 وفي منتصف الطريق الا انه أفضل من ايران على سبيل المثال ولكن ليس أفضل من الكويت أو المغرب أو لبنان أو البحرين أو مصر أو الاردن أو عُمان. هذا ليس مشجعاً.

وبما ان الوقت ثمين والبلدان تتنافس باستمرار في المجالات الاقتصادية، فالبنك الدولي ينشر بيانات حول بناء الاعمال الاقتصادية والتجارية من حيث علاقتها بالوقت.  ففي الجدول اعلاه نرى ان بناء مستودع في العراق يحتاج الى سنة من الوقت، وحوالي سنتين لتطبيق عقد تجاري معين، و شهرين للحصول على كهرباء، وشهرين لغرض تسجيل شركة...وعند المقارنة مع دول الريادة مثلاً نيوزيلندة، نجد انه يمكن تسجيل شركة واجراء كل المتطلبات والبدء بالاعمال التجارية في يوم أو يومين حسبما ورد في بيانات البنك الدولي.

ان هذه البيانات تلخص الوضع الاقتصادي في العراق بعد 2003. ببساطة متناهية: ليس هناك تطور.