The biggest problems, however, appear to lie in the impact of prices on the global economy. From a global perspective, total energy costs are about 10 per cent of global gross domestic product, a level last seen in the late 1970s. In the US, oil costs are above 4.5 per cent of GDP and for the world as a whole oil spending is 5.4 per cent of GDP, both creeping up to the record world level of 7.3 per cent.Does anyone have a time series of world energy costs vs. GDP?
The Science and the Politics of Disasters and Climate ChangeThe talk on March 2 will set the stage for a second talk I will give on April 9 in which I will discuss the ethics and responsibilities of doing science in the context of a highly politicized issue like climate change. You don't need to come to the first talk to make sense of the second, but it might be helpful background as I will draw on the case study. (I wonder if there are other recent examples of issues arising at the interface of ethical responsibilities and climate science that I might draw upon? Any ideas?)
Friday March 02, 2012. 03:30 pm. IBS Building, room 155, University of Colorado
Roger Pielke, Jr.
University of Colorado, CIRES Fellow, Center for Science and Technology Policy Research, and Environmental Studies Program
Refreshments following lecture on the IBS patio
April 9 at 12:00 PM
WAG THE DOG: ETHICS, ACCURACY AND IMPACT OF THE SCIENCE OF EXTREMES IN POLITICAL DEBATES
Roger Pielke, Jr.
Location: CIRES Auditorium
Some argue that strong productivity growth has caused much of America’s manufacturing job loss, especially in the last decade. This theory, which contends that technology is replacing workers, stems from the observation that apparent productivity gains have coincided with manufacturing job loss in the 1990’s and 2000’s. Yet there is no economic reason why increased productivity must lead to job loss.The first thing to note is that Brookings is talking about overall productivity gains, and not labor productivity. The different is important. Labor productivity according to the BLS "is the ratio of the output of goods and services to the labor hours devoted to the production of that output." Overall ("multi-factor") productivity "relates output to a combination of inputs used in the production of that output, such as labor and capital or capital, labor, energy, materials, and purchased business services (KLEMS). Capital includes equipment, structures, inventories, and land." The distinction is crucial to understanding employment changes in manufacturing.
Even though a productivity increase means that fewer workers are needed to produce a given quantity of output, the productivity increase also allows product prices to be lower, increasing the size of the product market. The bigger market means that firms will need to hire more workers. The additional hiring needed to produce for a bigger product market usually offsets the initial labor-saving impact of the productivity increase. Therefore, the overall impact of a productivity increase is usually to expand employment rather than reduce it.To see where Brookings has erred, think about the mathematics here -- If a market for a good expands that means that more output is required. Additional labor needed to meet that demand is an input. If the magnitude of the change in the input is equivalent to the magnitude of the change in output, then there has in fact been no increase in labor productivity, which is defined as an ability to produce more with fewer hours on the job. If labor productivity is improving then the inexorable result will in the long run be a loss of jobs, even in an expanding market. In the short term, market expansion can offset job losses, such as we are currently experiencing in the US, but only temporarily. In short, with respect to jobs, simple math tells us that market expansion cannot defeat labor productivity. Just look at agriculture for an example of this dynamic (e.g., programs such as the Food for Peace effort of the 1950s were designed to expand markets in the name of aid and diplomacy).
Under a more appropriate methodology the proper conclusion is that the "flashing crosswalks" have a much higher accident rate than non-flashing crosswalks -- the exact opposite of the City's conclusion. Thus, a poor quantitative analysis can do more to mislead than to clarify. This clear and simple example will be part of my graduate seminar quantitative methods of policy analysis the next time I teach it.[T]he city recently released their Safe Streets Boulder Report, in which they quite correctly note that a very large number of the accidents between motor vehicles and either a pedestrian or a bicyclist occurred in crosswalks at intersections, and a rather smaller number occurred in the flashing crosswalks. Moreover, I don't doubt their arithmetic was correct when they converted those accident counts to percentages.
On the face of it, the report's finding that 37 percent of the pedestrian/bicyclist-vehicle accidents were in crosswalks at intersections while "only" 6 percent of such accidents were in flashing crosswalks seems to be evidence that the flashing crosswalks are statistically more safe than anyone thought, and that if anything we should be worried about the crosswalks at our city's intersections.
Unfortunately those numbers are profoundly misleading.
You see, the report doesn't mention that there are only a few flashing crosswalks in the entire city (only 18 have ever been installed). However, there is a very large number of the crosswalks at intersections -- four at almost every intersection, totaling hundreds if not thousands across the city. So it is not terribly surprising that the city found a smaller number of accidents in a very small number of flashing crosswalks, while there were a larger number of accidents in the much larger number of crosswalks at intersections.
To correctly compare the safety of flashing crosswalks with those at intersections, one needs to know the accident rates for each type of crosswalk.
The memo doesn't add new facts, just new spin. Naturally, because the spin is more lurid, it's what a lot of the climate blogs seized on.If the faked document happened to be produced by a climate activist or scientist (as some are already suggesting), then the leaked Heartland documents will go down in history as one of the more spectacular own goals in the history of the climate debate (with the consequences proportional to the stature of the faker). The faking is likely to overshadow whatever legitimate questions may have been raised by the release of the documents. Imagine what would have happened if the UEA hacker/leaker had made up a few emails to spice up the dossier.
Historical global tropical cyclone landfallsIn the paper we provide details on landfalls of tropical cyclones (called hurricanes in the Atlantic) for the five major global basins and a global aggregate from 1970 (in the figure shown above -- the paper provides similar graphs for each of the basins for the periods of available data). We take the Atlantic back to 1944 (no other basin has reliable data before 1950, so earlier data is superfluous for our analysis), though the record of US landfalls goes back before 1900 and has been discussed in other papers (like this one in PDF). Tropical cyclone statistics are a cherry picker's delight because large intra-basin variability means that "trends" can be found (up and down) over various arbitrary periods of record. For instance, we do see a upwards trend in North Atlantic landfalls since 1970, but not since 1944 (or 1900). Other basins show similar up-and-down pattens on multi-decadal periods, but we finding nothing coherent at the global level. Over 41 years of reliable data, there is precious little evidence of a secular trend at the global level.
Jessica Weinkle, Ryan Maue and Roger Pielke, Jr.
Journal of Climate (in press)
In recent decades, economic damage from tropical cyclones (TCs) around the world has increased dramatically. Scientific literature published to date finds that the increase in losses can be explained entirely by societal changes (such as increasing wealth, structures, population, etc) in locations prone to tropical cyclone landfalls, rather than by changes in annual storm frequency or intensity. However, no homogenized dataset of global tropical cyclone landfalls has been created that might serve as a consistency check for such economic normalization studies. Using currently available historical TC best-track records, we have constructed a global database focused on hurricane-force strength landfalls. Our analysis does not indicate significant long-period global or individual basin trends in the frequency or intensity of landfalling TCs of minor or major hurricane strength. This evidence provides strong support for the conclusion that increasing damage around the world during the past several decades can be explained entirely by increasing wealth in locations prone to TC landfalls, which adds confidence to the fidelity of economic normalization analyses.
Our challenge is not building a new satellite, but to rebuild our economy. If the recession has taught us anything, it is that we cannot go back to an economy driven by too much spending, too much borrowing, and the paper profits of financial speculation. We must rebuild on a new, stronger foundation for economic growth. We need to do what America has always been known for: building, innovating, and educating. We don’t want to be a nation that simply buys and consumes products from other countries. We want to create and sell products all over the world that are stamped with three simple words: “Made in America.”The invocation of manufacturing's golden age is bipartisan, with Mitt Romney recently making a speech on a factory floor and promising to bring back manufacturing jobs.
When asked which industries are most important to the national economy, manufacturing is near the top of the list, topped only by energy. Eighty-six percent indicate that America’s manufacturing base is “important” or “very important” to our standard of living. And when asked if they could create 1000 new jobs in their community with any new facility, manufacturing comes in at the top of the list – ahead of energy production facilities, technology development centers, retail centers, banks or financial institutions and a host of others. . . Seventy-nine percent of Americans believe a strong manufacturing base should be a national priority.The poll also provided some evidence that the world has changed:
While the U.S. public registers a strong belief in the importance of manufacturing for the country’s economy, when it comes to choosing manufacturing as a career choice, they place it near the bottom of the list. Out of 7 key industries, manufacturing ranks second to last as a career choice. While the reasons for this are complex, one interesting finding suggests that Americans (77%) fear the loss of domestic manufacturing jobs to other nations, contributing to a sense that manufacturing is an unstable long-term career choice. Of equal concern is the fact that the future talent pool is least excited about the prospect of a career in manufacturing. Among 18-24 year-olds, manufacturing ranks dead last among industries in which they would choose to start their careers.
It is important to separate as far as possible the role of expert knowledge generation and evaluation from the role of those charged with policy formation. Equally, it is important to distinguish clearly between the application of scientific advice for policy formation (‘science for policy’) and the formation of policy for the operation of the Crown’s science and innovation system, including funding allocation (‘policy for science’). This paper is concerned with the former. A purely technocratic model of policy formation is not appropriate in that knowledge is not, and cannot be, the sole determinant of how policy is developed. We live in a democracy, and governments have the responsibility to integrate dimensions beyond that covered in this paper into policy formation, including societal values, public opinion, affordability and diplomatic considerations while accommodating political processes.Very smart stuff.
Science in its classic linear model can offer direct guidance on many matters, but increasingly the nature of science itself is changing and it has to address issues of growing complexity and uncertainty in an environment where there is a plurality of legitimate social perspectives. In such situations, the interface between science and policy formation becomes more complex. Further, many decisions must be made in the absence of quality information, and research findings on matters of complexity can still leave large areas of uncertainty. In spite of this uncertainty, governments still must act. Many policy decisions can have uncertain downstream effects and on-going evaluation is needed to gauge whether such policies and initiatives should be sustained or revised. But, irrespective of these limitations, policy formed without consideration of the most relevant knowledge available is far less likely to serve the nation well.
How can the U.S. dig itself out of the current job drought? Government policy can temporarily boost employment. The ultimate answer, though, is innovation: The creation of new goods and services that spur the growth of new industries capable of employing tens or hundreds of thousands of workers.1The methodology is rough -- one could easily justify a number half as big or twice as large. In either case, the job numbers are big. The numbers are rough estimates because government economic data is not yet caught up with this fast-changing aspect of the national economy.
Nothing illustrates the job-creating power of innovation better than the App Economy. The incredibly rapid rise of smartphones, tablets, and social media, and the applications—“apps”—that run on them, is perhaps the biggest economic and technological phenomenon today. Almost a million apps have been created for the iPhone, iPad and Android alone, greatly augmenting the usefulness of mobile devices. Want to play games, track your workouts, write music? There are a plethora of apps to choose from, many of them free.
On an economic level, each app represents jobs— for programmers, for user interface designers, for marketers, for managers, for support staff. But how many? . . .
The App Economy now is responsible for roughly 466,000 jobs in the United States, up from zero in 2007 when the iPhone was introduced. This total includes jobs at ‘pure’ app firms such as Zynga, a San Francisco-based maker of Facebook game apps that went public in December 2011. App Economy employment also includes app-related jobs at large companies such as Electronic Arts, Amazon, and AT&T, as well as app ‘infrastructure’ jobs at core firms such as Google, Apple, and Facebook. In additional, the App Economy total includes employment spillovers to the rest of the economy.
Romer’s op-ed gets at least four critical points flat wrong. First, it conflates having a coherent set of policies and strategies to support U.S. manufacturers with them receiving “special treatment.” Second, it wrongly argues that manufacturing jobs are the same as all other jobs in the economy. Third, it misdiagnoses the central challenge facing the U.S. economy as a lack of aggregate demand when the real problem is faltering U.S. competitiveness, especially in the traded sectors of the economy, such as manufacturing. In doing so, her op-ed fails to recognize that the loss of manufacturing jobs has contributed significantly to the loss of U.S. employment, in terms of both direct and indirect jobs lost. Finally, arguments like this that manufacturing in the United States deserves no specific policy focus refuse to acknowledge the sophisticated strategies that dozens of U.S. competitors around the world have put in place to bolster the competitiveness of their manufacturing sectors.I'll address some of Ezell's points in detail in forthcoming posts, as the Romer vs. Ezell perspectives are examples of a larger debate on manufacturing, innovation and the US economy. Let me preview my two cents by suggesting that Romer is more right than ITIF on this issue.
On the whole, however, it seems fair to say that so far there is not yet much evidence for climate change as an important driver of conflict.
The IPCC is currently working on its Fifth Assessment Report, scheduled for release in 2013. For the first time, this report will have a chapter on the consequences of climate change for human security, including armed conflict (IPCC, no date). We hope that the studies reported here will contribute to a balanced assessment by the IPCC, built on the best peer-reviewed evidence.That such a statement has to be made is a statement itself.
Where is she wrong?As an economic historian, I appreciate what manufacturing has contributed to the United States. It was the engine of growth that allowed us to win two world wars and provided millions of families with a ticket to the middle class. But public policy needs to go beyond sentiment and history. It should be based on hard evidence of market failures, and reliable data on the proposals’ impact on jobs and income inequality. So far, a persuasive case for a manufacturing policy remains to be made, while that for many other economic policies is well established.
Whatever its findings, the [Queensland flood investigation] report will be more informative and comprehensive as a result of the inquiry being reconvened and extended for 13 days after The Australian exposed glaring inconsistencies in the original evidence given by SEQWater and flood engineers about serious breaches of the dam's operating manual over two days leading up to the disaster. . .Whatever one might think about the political views found on the pages of The Australian or feelings about its ownership, Australians have been well served by its dogged reporting in the case of Wivenhoe. For everyone, the case provides a good example why independent oversight of experts and government makes good sense.
For the public, an alarming aspect of the issue is that the mismanagement was uncovered not by their elected representatives or through the initial inquiry hearings, but by senior journalist Hedley Thomas's painstaking reading of official records. These suggested that SEQWater remained locked into the wrong strategy over the weekend of January 8 and 9 and into early Monday before the Brisbane River first broke its banks on January 11.
Scepticism, scrutiny of records and refusing to accept official spin are the hallmarks of fine journalism. Four days after the river peaked, contrary to SEQWater's insistence that the operating manual had been followed, Thomas questioned why the operation of the dam failed. He also reported independent engineer Michael O'Brien's view that catastrophe would have been avoided if releases had been adequate. Such probing, alas, did not suit more gullible media outlets, including Crikey, which brushed the public interest aside in claiming our coverage was "distorted" by "out-of-control" ego. A year on, the operations manager and chief executive of Queensland's WaterGrid admit that, based on what they were told at the time, the dam was mismanaged for two crucial days before the floods. In a land of climate extremes, hard lessons have been learned about managing the ravages of floods as well as drought, and the evacuation of St George shows authorities are being proactive. The emergence of the truth about Wivenhoe is also a lesson about public-interest journalism.
The normalised loss figure shown above is an updated version of that published in Crompton and McAneney (2008). The methodology used to normalise losses has been refined and the loss data from seasons 2006/07 - 2010/11 has been included and normalised to season 2011/12 values. The Insurance Council of Australia (ICA) insured loss data is current as at 31/1/12.
In our previous normalisation of the Disaster List ending at the 2005/06 season (Crompton and McAneney, 2008) we noted the low loss activity in the most recent 5 seasons analysed. Since that time there has been heightened weather-related loss activity with the most recent 5 seasons to 2010/11 averaging slightly more than double the 45-year average. The average annual weather-related insured loss over the most recent 10 seasons (2001/02 – 2010/11) is within approximately 30% of the average annual loss over the full 45-year period of the Disaster List.
In a series of heated exchanges at Queensland's recalled floods inquiry yesterday, SEQWater's principal engineer of dam safety, John Tibaldi, was grilled over a report he penned in the weeks following the January floods, which accounted for the actions he and his fellow engineers took.Apparently SEQ Water is privately insured, though for what contingencies and to what financial level it is not clear from what I have read. What does seem increasingly clear is that someone is going to receive a big bill to settle what will inevitably be large claims against SEQ Water. Stay tuned.
At one point, Mr Tibaldi choked up in tears under the questioning.
Commissioner Cate Holmes, a Supreme Court judge, reconvened the inquiry after The Australian revealed evidence that appeared to show the dam was employing less severe flood mitigation strategies than those detailed in Mr Tibaldi's report.
As well as SEQWater officials and engineers being called to testify, Premier Anna Bligh has been asked to submit a written statement to the inquiry. Ms Bligh said she would provide a comprehensive statement by Monday and would submit a copy of her diary and relevant documents relating to the meetings and briefings she attended at the time of the floods.
Mr Tibaldi told the inquiry the report used raw data collected during the flood -- including lake levels and outflows -- and he then matched the data to the release strategies prescribed in the dam manual, known as W1, W2, W3 and W4. He said he had no recollection of asking the three other dam engineers which strategies they were using at various times during the disaster, but prepared the report based on the raw data and subsequently sought their approval.
"I tried to match the strategy transitions against the data that was available to me (and) just made conclusions based on that data as to when strategy transitions had occurred," he said.
Counsel assisting the inquiry, Peter Callaghan SC, suggested the manual was therefore used to analyse and justify the decisions taken by the four engineers -- Mr Tibaldi, Robert Ayre, Terry Malone and John Ruffini -- rather than dictating the decisions they took at the time.
