Russia Growth Diagnostics (5): Uncertainty

< Part 4: Infrastructure and Human Capital

While checking for government failures, I closely follow HRV (2008), who break the failures into three groups: ex ante risks, taxation, and law enforcement. Let’s start from the first group.

Uncertainty and Investments

Ex ante risks refer to the volatility of expected returns to economic activity. Low expectations reduce investments and growth slows down. Here I discuss only the risks associated with government actions (or inactions).

We should distinguish these risks from the risks arising in particular economic activities. Acemoglu and Zilibotti (1997) developed a model in which agents are unable to invest profitably because of scarce diversification opportunities. Instead, agents choose low-risk activities, which don’t create stable growth. While this model is intended to explain the surprising economic uprising after 1800, it can also describe some modern economies. Some, but not Russia’s.

Russia has enough economic opportunities for diversification and a financial system capable of implementing it. Industry-related risks can be mitigated. Then the candidate problem is a sort of uncertainty that affects the entire economy.

How does this uncertainty affect growth? The results in the literature are sensitive to model specifications. I exemplify it with a simple regression of annual growth on volatility of growth (where I take only the period starting at the dissolution of the Soviet Union):

growth_f_volay

A strong connection appears only in the OECD sample. For control, alternative models, and more coherent coverage of the topic, I recommend Jones and Manuelli (2005).

An informative, but limited, perspective comes from investments in fixed capital: buildings, machinery, and other things that last. In an uncertain environment, we expect investments in fixed capital to fall.

gdi_gdn

The stagnation of investments continues in BRICS and G7 since 2008. For Russia, I included the private sector to indicate that not government alone supports this level (though national accounts treat state-owned enterprises as private). You can look at FDI, which fell sharply in the recent years, but hot money and parent companies in offshores make this indicator even less informative than domestic investments.

The overall stagnation is not bad (in the meantime, Greece halved investments in fixed capital to take an example of bad expectations). Yes, government spending and procurement are responsible for maintaining this level, but while speaking about uncertainty, the efficiency of spending is a separate question.

Testing Constraints

Political and social risks. Business worried about these risks right after the 2008 crash (see BEEPS 2009), but calmed down by 2013 (see that year’s BEEPS). Can worries significantly constrain growth? Declining investments would be the major channel in this case, but we saw that this channel was okay. This may change after 2014, so we’ll see.

Tax policy risk. Expectations of higher taxes are justified because one half of government revenues comes from taxes on natural resources. Commodity prices fall and government has to compensate the loss of revenue by increasing taxes on consumption and income.

Labor market risks. This is relevant mostly for households that may expect unemployment and reduce consumption in advance. Unlike the United States, where adjustments happen mostly through unemployment, the Russian economy more actively enables two other channels: working hours and real wages. These are milder forms of shocks, though at the expense of overall productivity. People pay less attention to the risk of losing the entire income and the impact on the current consumption (and growth) is small.

History of expropriation. There’re expropriation cases similar to what happens in some Latin American countries. In Russia, expropriation is limited and selective, and so is its impact on growth.

Macro uncertainty. Oil prices affect exchange rates, which, in turn, change costs in import-dependent industries, such as manufacturing. Commodity prices directly affect the revenues of exporters. The large trade flows aggravate these effects. The composition of trade implies volatility as the export side consists of commodities, half of which is oil.

Each of these five tests shows a positive result, so uncertainty hinders growth in Russia. This idea is reinforced with the difficulties of securing long-term financing (see the other post). Even if businesses have high returns or sound business plans, investors adjust these returns for the economy-wide uncertainty and reject requests for funding.

Alibaba, The State

Alibaba is sort of doing fine after the IPO. But what does it do? It replaces the state.

Roughly, if a firm picks a supplier, it wants supplies to be fine and to arrive in time. The supplier, in turn, want to make sure that the client pays as agreed.

Now, there are two ways to provide it for sure. Option A is the threat of legal actions if things went terribly wrong. Option B is to avoid bad partners at all. The state offers both options. It has licensing and regulators to prevent very bad companies from operating in the market. And the state also has a more traditional function of bashing bad businesses for violating the law.

Obviously, Alibaba is not the British East India Company—it cannot apply violence freely. But it does offer an alternative to government regulations, especially in countries where governments are not trusted. The website routinely offers inspections and secure payments. It encourages buyers to leave feedbacks. As a matter of punishment, it can ban businesses from the marketplace.

Alibaba reduces the risk, which would otherwise require more resources to meet. Though private inspections, insurance, and feedbacks have been there for centuries, IT technologies made them extremely centralized and embedded in a single company. The state also implies a monopoly—and online marketplaces have it! Amazon, eBay, and Alibaba have no strong competitors in their respective markets.

Does this replacement for weak governance affect economic development? Possibly. Alibaba is an international trade hub. Normally, small and medium enterprises are reluctant to deal with international partners due to uncertainty. For example, the World Bank points at political risks:

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Those investors who actually work in emerging markets estimate the risk as being three times lower than that by investors who don’t consider investing in emerging markets at all. Uninformed investors overstate risks and stay away from what can be a perfectly normal market.

Many of the B2B transactions mediated by Alibaba might not have happened at all without the relevant information. For one reason, the baseline risk is high as governments in emerging markets are reluctant to prosecute local crooks. For another, western mass media cover these markets biasedly. Someone who read the Financial Times throughout 2014 might have an impression that China is nothing more but corruption, political trials, empty infrastructure, ghost cities, and permanently slowing down economic growth. Even if these materials are not necessarily biased against one country (the media look for a drama everywhere, right?), the readers can’t simply go out in the streets and check how things really are, as for domestic coverage. Therefore, businesses need a middleman who is more motivated than the state and more systematic than the media in helping shoppers in emerging markets.

Die Each Day As If It Was Your Last

“Live Each Day As If It Was Your Last” quote wanders around for a while, so here’s a quick thought on this.

First, those living their days as their last don’t live well. The poor in developing countries face many life-threatening risks. These risks make their ordinary days more like their last days. Technically, it means lower discount rates:

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An annual discount rate stands at 8–15% in developing countries and at 3–7% in developed ones. Since the rate discounts exponentially, poor nations basically ignore the future.

Short-sighted decisions, which high discount rates are about, hurt the present. Families save less, banks have fewer deposits, businesses borrow and hire reluctantly, so the economy grows slowly and incomes stagnate. People avoid long-term commitments because they don’t expect to live that long. In street terms, the last-day thinking leads to more crimes, less education, and post-apocalyptic surroundings. How about wages equaling 1/10th of those in Europe and US?

Europe had them in the Middle Ages. The Church tried to raise the discount rate artificially by promising eternal existence. (“And they will go away into eternal punishment, but the righteous will go into eternal life.”)  The attempt didn’t impressed the congregation, which sinned like crazy. After all, the problem was solved differently.

For this, it’s even more surprising to hear the last-day advice after all these years of hurting experience.

Getting things done: startup edition

Publicly available startup data includes firms that exist just as online profiles. So, maybe these firms will do their product some other time or they will disappear. It’s better to exclude such startups from stats and look at who survives.

Funding is a good filter here. Getting seed funding means a startup at least has a team and idea. But over the years, the fraction of series A deals decreases:

If a smaller fraction of startups gets next-stage funding, it means that fewer startups survive after getting seed money. This survival rate indicates how well startups get prepared for doing business. The fewer firms lost on the way, the lower risks investors bear.

The major startup nations from CrunchBase:

China and Israel do well here. The US makes other countries look like dwarfs on charts, so it has a separate graph:

About 80% of startups live their first to fifth funding stage. Having more stages isn’t that common. By the later stages, a startup either becomes a company with more conventional funding (revenue, bank loans, bonds, public equity), or gets acquired by another company, or disappears.

Replication files: https://github.com/antontarasenko/blog-replication-files/tree/master/2014-09/08_cb_funding_stage

Investing and failures in startups

The efficient market hypothesis got a bad press after 2008. Not surprisingly. It’s a half-truth. For instance, what Robert Shiller identified as genuine mispricing Robert Lucas called a minor deviation. Also, the hypothesis has many interpretations, and here’s one of them.

(data link)

On the left we have the mean of money that startups received over their lifetime. On the right is a rude measure of risk: the ratio of acquisitions to closed companies in the respective market. So, enterprise software has three successful acquisitions per one failure. I dropped “operating” startups because it’s difficult to interpret their success.

The graph is interesting because clean tech gets much funding but has one acquisition per two failures. Analytics gets small funds (not so sexiest as it was called?), but gives very stable outcomes. These two are exceptions because in general funding match the risk measure. And so in other markets: it’s enough for one product (like housing) to have abnormal pricing for the entire market to be under risk.

That is an attempt to make complex things embarrassingly simple, of course. For example, some may insist that average funding is a measure of capital intensity, not of competition among investors. Or what we should honestly calculate returns, as was done here. But it all seems to be half-truths, including this piece. We have to keep watching.