Climate Change and the New Zealand Economy

Global warming is a fact. Figure (1) plots the average change in Global, Northern hemisphere and Southern hemisphere temperatures from 1880 to 2018 (reference). The temperature has been rising, more so in the Northern Hemisphere. 

Figure (1) 

The standard economic story is that global warming increases the cost of production of food and primary commodities, reduces their supplies, and as demand keeps rising, the price of commodities increases (excess demand).[1]

Figure (2) plots the ANZ bank, New Zealand’s commodity price index and the World commodity price index (it includes meat, skins and wool; dairy; horticulture, forestry, seafood and aluminium).

Note that both prices increasing as predicted, but the New Zealand commodity price is often lower than the world’s commodity prices.

Figure (2) 

Based on such information, The New Zealand Agricultural Greenhouse Gas Research Institute concludes, “Climate changes could further drive up international commodity prices. That in turn would benefit New Zealand farmers and agricultural exports.”

Figures (1) and (2) clearly imply that the New Zealand commodity price level (as measured by the commodity price index) is positively correlated with global average change in temperature (both rising). This is also true for the price of every commodity in the index (meat, dairy...etc.). However, the conclusion of the Institute is misguided because the demand for New Zealand’s commodities depends, not on the New Zealand commodity price alone, but on both, the New Zealand price and the world’s price.

How is that?

What matters for the demand on the New Zealand primary commodities is not the New Zaland commodity price per se, but rather the relative price that is the ratio of the New Zealand commodity price to the world’s price of the same commodities.

Figure (3) plots the data from Jan 1986 to Mar 2019. The correlation is negative.

Figure (3) 

In a global commodity market, a change in the nominal price of a NZ commodity exerts two effects on the quantity demanded of New Zealand primary commodities. First, it changes the relative price, which is a change in the terms at which a global buyer can exchange a NZ commodity for another non-NZ commodity (e.g., New Zealand’s dairy and the other countries dairy). The change in the relative price leads to a substitution effect. A lower relative price increases global demand for New Zealand’s commodities. Second, there is an income effect. A change in the nominal price of New Zealand’s commodity causes a change in real income of the buyers, or in the size of the basket of primary goods, a global buyer can buy. If global warming causes the price of a New Zealand commodity to fall, all other prices remained unchanged, the consumer’s real income rises because more of such good, or other goods, could be purchased.

Assuming that everything else remains unchanged, the patterns depicted in figure (2) remain as such under global warming, the higher the New Zealand’s productivity (in primary commodities sector) is, the lower our relative commodity prices, and the higher the global demand on our commodities.

Furthermore, although commodity prices are highly volatile, they still share significant cyclical fluctuations with nominal GDP. They are also positively correlated with expected inflation. I showed that changes in relative commodity prices fully explain the Kiwi dollar depreciation rate Razzak, 2018. Global warming is very relevant to economic policy; see Rudebusch 2019 (here).     

Global warming is clearly a danger and a game changer. The economic analyses I have seen so far are thin. Policymakers need a more general equilibrium analysis to understand the costs and the benefits. There must be some benefits, I do not know what they might be. I can imagine that truism might benefit from warmer temperature. Farmers might be able to produce new varieties that they could not produce before, hence opening new markets. 

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[1] Google for example, How Climate Change Will Alter Our Food; How Climate Change May Affect Global Food Demand and Supply In the Long Run; and Roundtable II: Economic Growth and Climate Change: Long Run Implications for Commodity Prices and Trade.

Corruption and Economic Growth

On March 19, 2019, the well-known American political scientist, Stephen Walt, wrote in FP (here) “corruption is inherently inefficient.” He explained, “Instead of resources going where they are most needed, they get diverted into bribes, payoffs, kickbacks, and other shady arrangements. And when the wealthy and powerful use connections to get jobs or contracts (or to get their kids into college), that means that more deserving and talented people get excluded and less qualified people end up in positions of authority. The more common such practices become the more honest and law-abiding people will be tempted to follow suit just to keep up. And once corruption becomes endemic in a society, rooting it out becomes difficult if not impossible.”

Economic research on the relationship between corruption and economic growth is relatively thin. Exceptionally, Isaac Ehrlich and Francis T. Lui (1999) paper in the Journal of Political Economy (here) explains the relationship rigorously and in a way, economists understand. They use endogenous growth models.

They arrive at a variety of results. Here are a few interesting ones.

·         “Accumulation of some political capital, hence corruption, is thus shown to be an inevitable aspect of government intervention in the economy.”

·         “… A given level of government intervention will be more harmful to persistent growth prospects in human capital–poor countries than in human capital–rich ones. The former can afford fewer ‘‘errors’’ in government policies. This implication seems contrary to conventional theories of development, which typically recommend more involvement of government in less developed countries.”

I think that more government involvement in less developed countries is, perhaps, needed in the early stages of development (building infrastructures, schools, hospitals etc).

·         “Corruption and per capita income level are expected to be negatively correlated across different stages of economic development. The difference is that corruption depends on investment in political capital as a ticket for entry to the bureaucratic rank, unlike entry to many criminal activities, which requires little skill. Such an investment has repercussions on the incentive of productive agents to invest in human capital. The relationship between corruption and the economy is thus explained as an endogenous outcome of competition between growth-enhancing and socially unproductive investments and its reaction to exogenous factors, especially government intervention in private economic activity.”

·         “The relationship between government, corruption, and the economy’s growth is nonlinear. Government intervention in private economic activity hurts most in the poorest countries and those at a critical takeoff level. This may explain the prevalence of corruption in countries trapped in poverty.”

·         “Perhaps the most intriguing result of the analysis concerns the possibility that autocratic regimes, such as the command economies, could in principle achieve a rate of growth equal to or higher than decentralized democracies, albeit not a higher level of per capita income. These economies can be successful as long as an informed leadership is operating to maximize the long-term growth potential of productive agents and constrains bureaucratic corruption to a degree commensurate with this objective. This explains why economically successful autocratic regimes often resort to forceful anticorruption campaigns and why corruption often intensifies when the leadership loses its grip on power. At the same time, the analysis also anticipates the potential failure of autocratic regimes because of the leadership’s inability to focus on long term goals, its susceptibility to ideologically induced policy errors, and the general deadweight costs associated with protecting an autocratic regime by brute force.”

I wrote in the past about the positive relationship between corruption and government regulation (here).  

I use the Corruption Perception Index (here). To illustrate Walt’s point graphically I took the average of the percentage change for the period from 2012 to 2018 for ten most advanced European countries and the USA (USA, Austria, Belgium, Finland, France, Germany, Italy, the Netherlands, Spain, Sweden, and the UK).

The percentage change in the corruption perception index for 11 advanced countries for the years 2012-2013 compared with 2017-2018 has declined in three countries (the US, UK, and Germany), more in the US and the UK and less in Germany. Although Walt’s argument is valid, the available data for the US do not show such increase in corruption. Maybe new data for 2019 and more future data would show what Walt is describing.

The index has not changed significantly in Sweden and Belgium; and increased in the rest of the countries (Spain, Italy, the Netherlands, Finland, Austria, and France) with France exhibiting the most significant increase.

Figure (1) plots the data.

Figure (1) 

Then I computed the average productivity growth and the average Total Factor Productivity growth (TFP) – a measure of economic efficiency – from the EUKLEMS 2017 data set. Productivity is real value added per hour worked. EUKLEMS publishes a TFP index. The samples are slightly different across countries, but most data cover the period up to 2015. For all data, I use the measure of what EUKLEMS refers to as the “market” instead of “total economy” whereby the government and the services such as education, health, etc. are excluded. Check (here).

Figures 2 and 3 plot the correlations of the percentage changes in the corruption perception with productivity growth and TFP growth.

Figure (2)

Figure (3)

Surely, the correlation between corruption and productivity growth is negative across the advanced countries. Thus, rising corruption is associated with lower productivity.[1]

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[1] Corruption is not the sole explanatory variable of low productivity. I have written on this before. There are measurement issues (e.g., Feldstein, 2017) and a population effect. Population data show significant decline in the growth rates of working age population, fertility rate, youth population, etc. in advanced countries. Thus, there are fewer people working on scientific research, which reduced global research output needed for economic growth. This trend is quite alarming in advanced economies. Robert Gordon (2016) argued that the days of high productivity in the US have gone for good. Fernald and Jones (2014) suggest that the U.S. future economic growth is likely to slow down because educational attainment and population are likely to slowdown in the future. They also argue that the shape of the idea production function introduces uncertainty into the future growth. They also suggest that the rise of China and India’s research growth, artificial intelligence, climate change, income inequality, and health care are among the variables that explain future productivity in the United States. Bloom et al. (2017) argue that evidence at the micro level US. data suggest that there has been an increase in global research efforts (i.e., the number of people in research) coupled with a sharp decline in research productivity. They say that it is getting harder to find a new idea.

Excessive regulations ==> more corruption ==> lower productivity growth