Hyperinflation, Currency Crises & Insurance Industry Collapse

Hyperinflation destroyed Zimbabwe’s insurance sector, and decades later, it still hasn’t recovered. Currency crises in Lebanon, Argentina, and Venezuela have crippled financial institutions, showing how fragile financial systems can be when trust in money itself disappears.

A recent discussion started as a tongue-in-cheek debate: Is inflation a more efficient way to raise revenue than taxation? But it evolved into a broader debate on monetary risk, Bitcoin, inflation, and long-term economic trends—and why so many common arguments deserve scrutiny.

How Inflation Impacts Insurance

Premiums & Inflation Risk
High inflation makes level premiums unworkable, erodes the real value of cover. Optional benefit increases create adverse selection problems in life insurance. Even constant percentage increases fail under volatile inflation, and real wage stagnation worsens affordability pressures.

Monetary Instability & Insurer Solvency
Currency collapses create huge challenges for insurers trying to meet liability obligations in real terms. When inflation spikes, reserves built on past assumptions become grossly inadequate, leading to solvency concerns and even industry-wide failure.

Crypto & Smart Contracts in Insurance
Blockchain has potential for parametric insurance, automated claims processing, and fraud reduction. But much of the excitement outpaces practical application—or solves problems that were already solved while not addressing key remaining challenges.
(And let’s be real—just because a smart contract auto-executes doesn’t mean lawyers won’t find ways to argue intent and “meeting of minds.†)

My (Cautious) View on Blockchain

I spoke at the 2016 ASSA Convention on Seductions of the Blockchain, and my position remains:

• Cautiously optimistic
• Interested in opportunities
• Frustrated by the lack of rigorous debate from both fanatics and skeptics

The fanboys see blockchain as a cure-all, while the status-quo-invested skeptics dismiss it entirely. Reality, as always, is more nuanced.

Key Arguments & Concerns

1 Inflation as an ‘Efficient’ Tax?

Some argue that taxes are administratively complex, difficult to collect, and inflation acts as an “invisible tax† that transfers wealth to the state with less friction.

The Problem? Inflation isn’t a neutral mechanism:

• Distorts price signals and makes long-term contracts unreliable.
• Increases uncertainty and raises borrowing costs.
• Disproportionately harms those without inflation-protected assets—often the poorest.
• Erodes trust in government’s ability to manage financial stability.

Hyperinflation isn’t just caused by overspending—it requires excessive money printing to cover deficits. Many governments (e.g., Japan, the US, and EU countries) have run huge deficits for years without hyperinflation because they borrow responsibly instead of monetising debt.

Friedman’s famous quote:
“Inflation is always and everywhere a monetary phenomenon in the sense that it cannot occur without a more rapid increase in the quantity of money than in output.”

2 Bitcoin as a Predictable Alternative to Fiat?

Bitcoin proponents argue that a fixed supply prevents inflation and provides monetary certainty. But there’s a flip side:

The Problem? A rigid money supply is deflationary, which discourages spending and investment:

• BTC expansion (~0.9% today, falling below 0.5%) is well below global population and economic growth.
• Fixed-supply currencies have historically failed because economies need monetary flexibility to adjust to shocks.
• A deflationary currency discourages productive investment. If BTC’s price is expected to rise, why spend it? Why take out a loan?

This is why almost all mainstream economists—from Keynesians to monetarists—support some level of controlled monetary expansion.

Academic reference: Friedman advocated rules-based money supply growth, not a hard cap. Even Hayek, a proponent of free-market money, acknowledged the need for adaptable monetary systems.

A bigger issue: Some crypto coins have fixed supply, but the total universe of crypto coins is unlimited. New projects, forks, and tokens emerge constantly, meaning there is no true scarcity at a system-wide level.

3 Credit Risk & Smart Contracts – Who Pays When the Funds Aren’t There?

Smart contracts don’t solve credit risk. Traditional insurers must hold capital reserves and meet solvency requirements to ensure claims can be paid. Smart contract-based insurance lacks an equivalent safety net—yet.

Key Risks:

• No Guarantee of Payouts: If a smart contract is underfunded, it can’t issue emergency capital or negotiate claims—it just fails.
• Over-Collateralization Isn’t a Perfect Fix: Many DeFi protocols require excessive collateral to mitigate risk, but this limits scalability and locks up capital inefficiently. Actuarial approaches to capital adequacy could provide a smarter balance.
• Cascading Failures in Market Shocks: A major market downturn can cause mass liquidations, leading to systemic failures—just like traditional financial crises, but with fewer stabilizers.

Future Opportunity:

• As DeFi regulation increases, some form of capital adequacy requirements (like Solvency II for insurers) may emerge.
• Actuaries and insurance risk experts could play a role in designing smarter DeFi risk models.

Final Thought: Smart Contracts Are an Exciting Tool—but They Need More Work

Smart contracts introduce new efficiencies, but they also introduce new risks:
They remove intermediaries—but also eliminate safety nets.
They change fraud risk—but introduce oracle manipulation risk.
They enable fast, automated transactions—but don’t guarantee funds will always be there when needed.

For insurance, finance, and risk management, blind reliance on smart contracts is dangerous. But recent advancements show promise:

• Regulators are starting to provide legal clarity.
• Hybrid smart contracts (automated + human oversight) are emerging.
• Decentralized oracles & improved collateral models are evolving.

The real opportunity? Combining smart contract automation with actuarial risk management principles to build more resilient decentralized insurance solutions.

Would love to discuss with those working in insurance, risk management, DeFi, and blockchain regulation.

#Inflation #Blockchain #BTC #ETH #DeFi #DistributedLedger #MonetaryPolicy #FinancialRisk #Insurance #RiskManagement #Actuary #Economics #LegalRisk #ParametricInsurance

I’ve had reasons to think about Nigeria recently, in general but also from an insurance market and acquisition environment. I’ve helped several investors looking at Nigerian insurers over the years. Familiarity with the market and the expectations of these investors has bred complexity rather than contempt. This isn’t an easy diagnosis of land of plenty or dystopian money pit.

Nigeria still presents a compelling opportunity with its expansive land, sizable population, youthful demographics, positive growth trajectory, and abundant natural resources. Beyond its renowned oil and agriculture sectors, Nigeria boasts a vibrant movie industry (Nollywood) and a robust financial services sector, albeit with banks making more headway than insurers. Wholesale and retail trade are the biggest contributors to economic growth. This dynamic mix showcases Nigeria’s diverse economic landscape and entrepreneurial spirit and an increased focus on the service sector over energy extraction and farming.

While Nigeria’s potential has long been evident, ongoing challenges test that optimism. 

Inflation (29.9% annual for January 2024) and currency depreciation (74% down against USD since January 2022) have impacted individuals and businesses, amplifying economic strains. The local impact of foreign currency denominated debt has ballooned due to Naira depreciation. Ghana’s recent default weighs on everyone’s mind.

Food security for many is now a significant risk. Infrastructure limitations persist, impeding the full realization of economic growth. High unemployment rates, coupled with security challenges and governance issues, have eroded public and investor trust. In the insurance sector, while some have some growth and success with new product lines, overall insurance penetration remains modest. Insurance adoption has not accelerated as rapidly as envisioned over the past decade or two

While Nigeria stands to gain from ongoing disruptions in the Middle East and related waterways, the nation’s oil and gas sector remains a double-edged sword—both a source of revenue and trouble. Given the historical challenges of theft and attacks on infrastructure, Nigeria may not be able to maintain let alone increase production to meet an increased demand.

The recent decision by Shell to exit Nigeria’s onshore oil sector highlights the substantial risks involved, not only to infrastructure but also to human life. As a significant portion of Nigeria’s economy is still reliant on the oil and gas sector, these developments raise concerns about potential prolonged challenges, affecting the economy and therefore adding headwinds to insurers growth aspirations.

Insurers can’t fix these challenges directly. They need to focus on perception and reputation, on paying claims and improving operational efficiencies. Some insurers are excited about mandatory health and pensions, to go along with mandatory cover for motorists, but these compliance push factors do little to promote trust in insurance unless servicing and claim payment are slick and reliable too.

Most of the growth that insurers have managed over recent years has related to growth in GDP rather than an increase in penetration. The sorts of sustained 20%+ real growth that attracts investors and revolutionises a market will not come from economic and population growth alone.

There are opportunities for growth. When someone cracks microinsurance distribution and costs, and reaps the rewards of brand awareness, that can unlock massive growth and profits over time. There are many uninsured vehicles that could be bought into the insurance net. Smaller group policies covering household help could meet a needs of employers and employees. Annuities are a growing product for some insurers, and may present a further way to accumulate assets and also demonstrate trust worthiness to the market. (On the flip side, a single failure of a provider of annuities will crush this market for decades.)

Insurers need to have a strategic plan to manage their business within the turbulent environment. Some of what’s needed:

• A focus on consolidation around key products, unsentimental views of product profitability and underwriting performance.
• Allocation of capital to products to demonstrate return on capital, or at least incorporating an appropriate cost of capital into performance measures.
• Clear separation of investment returns generated on shareholder assets when understanding operating performance. (Warren Buffet’s words can be on “the float” misconstrued to destroy shareholder value.)
• (While you’re at it, it’s way past time to carefully segregate portfolios and match or at least hypothecate assets to specific purposes.)
• Clear-eyed evaluation of participating products. Customer expectations, levels of fees and charges. Fair investment returns and bonuses. The aim is to grow trust over time and wealth for your policyholders. Performance for shareholders will come.
• In general, a greater proportion of premiums must be used for benefit payments to policyholders, distribution costs must be contained, and expenses must be decreased. This is necessary to drive customer value and build trust, while leaving space for returns to shareholders.
• A better understanding of the role and benefit of reinsurance in life insurance. Different structures and different retentions may provide better results than rolling over similar structures indefinitely.
• A Digital Distribution and Servicing Strategy than recognises the trust deficit insurers have to work with and constantly pushes that flywheel to build trust rather than just drive the next sale. Customers want ready access to policy information and up-to-date account balances and policy status. On the back end, a single view of customer is required, giving customers and servicing agents the ability to update details once – and then use those details for effective, useful communication to policyholders. The more self-service possible the more empowered customers will feel.
• Recognition that driving down unit expenses (per policy expenses) is necessary for profitability and customer value. And decreasing unit expenses requires economies of scale. And that economies of scale requires BOTH scale and low variable costs – which is a function of automation, Straight Through Processing, Standard Operating Procedures and streamlined products.

Nigeria presents an opportunity, but it’s not without risks. The time necessary to realise investment objectives may be longer than is palatable to many, and disinvesting in difficult times often leaves a bitter taste and a lightened pocket.

Focus areas will differ by entity, but based on my experience, the points above are a sensible starting point for most. Add the controversial elements of tax rule application consistency and greater market conduct regulation and Nigeria’s market could really begin to take off.

What impact will the loss of Bitcoins over time have on the economy?

Why Bitcoin as a national currency will damage the economy

One of my concerns with Bitcoin as a national or universal currency is actually something proponents claim as a benefit. There is a finite number of Bitcoins that will ever be available. At the moment, the increase in the supply of Bitcoins is a positive number. Even with that, due to hoarding of Bitcoins and a little bubble mania, the price of virtually everything measured in Bitcoins is experience hyper deflation. (If that sounds odd, spend a minute thinking about it. We are used to thinking of the price of Bitcoins in Sterling or USD or ZAR, rather than the price of eggs or houses in Bitcoins.)

Deflation

Deflation of prices measured in Bitcoins is virtually assured in the long term, provided the global economy continues to grow. More stuff being bought, more services provided, more people being paid, more assets existing being chased by a finite number of bitcoins will lead to deflation. Which in turn leads to hoarding, unavoidably high real interest rates and contractionary pressure on the economy. This is a slice of Japan over the last 30 years.

But… negative interest rates?

We have limited negative nominal interest rates in certain markets at the moment. To be fair, this was unexpected when it happened some years ago, but is now relatively normal. Not all of the reasons for negative interest rates in Euro denominated sovereign bonds will apply to Bitcoin though, so I don’t believe that will be an out from high (positive!) real interest rates.

Alternative view, Bitcoins are infinitely substitutable

The aside I traditionally make at this point is that Bitcoin can have infinitely many substitutes. So the risk may be one of deflation, but could also be of eventual progression to nil value due to substitutes.

What to do about lost Bitcoins?

Now onto the point of this post. Bitcoins get “lost” all the time. You lose your wallet encryption key and the Bitcoins are gone forever. With fiat currency, the total money supply can be managed so that if somehow a fire burnt up a meaningful part of the money supply, more money could be created. It would still be a loss for those who lost the money, but at least the economy wouldn’t have to stumble along with a decreased money supply indefinitely.

If Bitcoins are lost at a positive probability per year, this will decrease the supply, adding to the deflationary problems described above. Yes, this is mostly an academic point because the targeted real rate of economy growth is likely way higher than the rate of loss of Bitcoins, so the contribution to the overall problem is small.

My suggestion? Do the world economy some good and give me your encryption keys for safe keeping. Just in case.

Non-life claims reserves are regularly not discounted, for bad reasons and good. This part of the series looks at the related issue of inflation in claims reserving. (You’ll have to wait for part 3 for me to talk about the analysis that prompted this lengthy series.)

In many markets, inflation is low and stable. Until a decade ago, talk of inflation wouldn’t have raised much in the way of deflation either. That’s still sufficiently unusual to put to one side.

Low, stable inflation means that past claims development patterns are mostly about, in approximate descending order of importance (naturally depending on class and peril)

• development of number of claims,
• development of claim estimates due to the reversal of initial conservatism (a typical but not universal practice), and in distance third place
• the impact of inflation of claims.

Similarly to discounting, one of the reasons inflation has such a small impact (especially when inflation itself is low) is that most claims for many classes are reported and paid quickly. This is clearly not true across all classes, and long tailed liability is an obvious counter example.

What the different common claims reserving methods assume about inflation

Basic Chain Ladder

Basic Chain Ladder assumes constant development patterns. Since inflation development contributes to development patterns the implicit assumption is that inflation is stable too. Strictly, we usually talk about “future inflation being a weighted average of past inflation” or similar.

Too many non-life reserving actuaries don’t spend enough time looking at the variability of and trends in development patterns before blindly following the methodology. Inflation isn’t the only variable that can disrupt past development patterns.

Bornhueter-Ferguson

Bornhuetter-Ferguson does the same, plus the addition of an initial or a priori estimate with even fuzzier implicit views on implied future inflation.

Most subjective assessments of assumed loss ratios will factor in a subjective view of inflation, most typically assuming it will continue as it has in the past. Practically, the choice of loss ratios to report on (accident year, underwriting year, financial year etc.) may also have an impact here.

Loss Ratio approaches

Simple Loss Ratio methods suffer the same fuzziness. We are assuming something about inflation, but almost certainly not explicitly so and I have never see a robust analysis of the impact of unexpected inflationary differences on loss ratios as feedback into Loss Ratio based reserving.

Average Cost Per Claim

Average Cost Per Claim (ACPC) methods have always appealed to me for their innate separation of development of number of claims from the actual amounts involved. (Don’t worry, I am firmly in the school of “apply many methods and understand the differences in results as part of building up a final estimate” rather than sticking with just ACPC.)

Apart from the ability to separate a pure IBNR from development of case estimates in an OCR (or Reported But Not Settled / RBNS to use a name that is less prone to being misunderstood) it also focuses the mind on the effects of inflation on individual losses.

It isn’t universally applied, but there is no reason not to apply a separate average cost per claim for different calendar years.

When it comes to an analysis of change in reserves, an Actual vs Expected comparison, there are plenty of good reasons to separate out number of claims and actual vs expectation inflation separate from the average underlying severity of claims that drives the final cost per claim.

Inflation Adjusted Chain Ladder

Then on to the Inflation Adjusted Chain Ladder (IACL). As a reminder, since it isn’t that commonly used in markets where inflation is uninteresting, the method is as follows:

1. Adjust past claim payments for past actual inflation (ideally using indices of claim costs or at least sub-indices that should closely follow claim costs) to put all claims in current money terms;
2. Use traditional triangle completion methods are followed to estimate real ultimate losses;
3. The final step is taking those future real claim payments and inflating them for future inflation. This naturally requires an estimate of future inflation.

Side note – impact of currency on inflation

In emerging markets, many parts and components are imported. This is true for motor, but also true for some property damage.

Rapid currency depreciations (Nigeria, I’m not only looking at you, but I am looking at you) can have a predictable impact on future claims inflation that might irk an efficient market proponent. There is no technical challenge here. Inflation is a time series process not a market price one – therefore we should expect inflation to be predictable.

The methodologies that allow for more explicit inflation estimates are better able to factor in the information about future inflation. Currency impacts are a clear example that should be factored into reserves, but cannot be if the inflation allowances are implicit.

Break even inflation, economist forecasts or last year’s inflation to predict future inflation?

This is worth an entire blogpost (or series) in itself. Estimates of future inflation should ideally be accurate, objective, directly related to the types of costs involved (rather than generic CPI), and easy to update.

Last year’s actual inflation isn’t bad for many of these measures. And often it’s surprisingly accurate. It doesn’t have the same actuarial panache  that more complex methods have though…. and yes when inflation isn’t stable it can give rise to poor estimates and poor decisions around reserve sufficiency and adjustment to future pricing based on experience analysis of incompletely run off periods.

What many don’t realise is that “break even inflation” or the difference between nominal and real “risk free” government bond yields is not an unbiased estimate of future inflation. It includes an inflation risk premium, typically positive, due to the imbalance of supply and demand for real risk-free investments to match real liabilities of pension funds, life insurers, and small portions of non-life insurers’ balance sheets.

In the same way estimates of CPI may need to be adjusted to reflect systematic differences to specific damage types or perils or just the inflation experienced by specific lines, so break even inflation based estimates also require adjustment before use.

Real estimates of claim reserves?

One methodology I saw adopted recently was a version of the IACL method where past claims were adjusted with inflation, development factors derived to estimate future real claims in current money terms, but then no future inflation and no discounting applied.

The actual face value of a reserve derived this was is not clearly wrong. By implicitly allowing for discounting equal to future inflation, this might be a reasonable proxy for investment returns that could actually be realised given a portfolio with plenty of cash and money market instruments included to bolster liquidity.  (See part 1 for a discussion on why a “risk free yield curve” may not always be a reasonable rate at which to discount claims reserves, at least not without adjustment.)

By now, you may gather that I don’t approve of the implicit nature of assuming future inflation and a reasonable, achievable discount rate will naturally offset. But, there is a more significant problem with this approach that I will cover in part 3.

This is part 2 of a 3 part series. Part 3 is here (not yet available).

A recent example relates to the common non-life practice of not discounting claims reserves.  Solvency II, SAM and IFRS17 moves to require discounting aside, it is still more a common GAAP approach to not discount than to discount claims reserves.

Discounting or fiddling with inflation has some obvious implications for analysing actual vs expected analysis, reserve run offs, and reserve adequacy analysis. That some non-life reserving actuaries trip over because it’s more natural in the life space.

But, first, why are non-life reserves so often not discounted? There are several reasons typically given:

• (1) Claim cash flows are too uncertain, therefore it’s not possible to know what term discount rate to apply.

This is mostly a weak reason. In insurance, all cash flows are uncertain to some or other extent. We are discounted expected values with an implied or explicit assumed probability distribution and will usually have some sense of the timing of cash flows. Large claims will cause noise in the analysis of timing and investment returns, but large claims will always cause more noise in the underlying underwriting performance anyway.

There is a link to point #5, which has merit in my mind.

• (2) Claim payment periods are usually short, so it doesn’t make a material difference to the result, while increasing complexity.

I’ll consider this combined with #3 below as they are closely related.

• (3) Interest rates are low, so it doesn’t make much difference.

Yes, discounting increases complexity. And where the claim development periods are truly short and interest rates are moderate or low, it might not be worth it.

Accounting has “materiality”, Solvency II and SAM have “proportionality” and most actuaries would apply some level of judgement around “significance”. Interestingly, none of these terms is usually well defined or, maybe more concerningly, consistently applied.

However, operating in a range of developing markets with inflation and discount rates anywhere from 3% to 25% means that even fairly short development periods can have a significant impact. The answer surely has to be “perform some quick testing to demonstrate the potential magnitude of the difference to inform a decision” rather than always just ignore it as a rule?

• (4) We want to be conservative and this introduces an element of conservatism.

This is an argument I have accepted before, but still isn’t the best way to handle this. If conservatism or profit deferral or market value margins are required, then the magnitude and run-off of these margins should be deliberate rather than arbitrary.

I’ve also seen versions of “We haven’t allowed for ULAE so these two offset, another version where the end result might not be that different but reflects a weak methodology subject to producing materially incorrect results if discounting and ULAE allowances begin to diverge.

• (5) Our actual investments need to be extremely liquid given the need to pay out large claims at short notice. Therefore we aren’t able to earn the yield implied by the yield curve. We don’t want to incur strains in future as our assets earn less than the unwind of the liabilities.

As I highlighted in #1 above, this is a real issue.  The operational and risk management necessity of maintaining sufficient liquidity, particularly in markets where the instruments used to derive the “risk free yield curve” are not necessarily liquid at all, causes a departure between the rates that theoretically (and naively) should be used to discount and what can actually be reasonably earned on backing assets.

How this issue is dealt with practically is a matter of applicable regulation and standards, professional guidance, past practice and documented policies, the purpose for which the results are being produced, and a good dose of judgement.

• (6) A related point to (5) is that insurers don’t want to show interest rate sensitive liabilities, especially when assets are not well matched.

Assets may not be well matched due to bad reasons, but also the need for liquidity, which in certain markets means duration = 0.

In part 2, how discounting and inflation adjusting interact. Part 3 will finally address the AvE, reserve adequacy analysis and impact on P&L.

Check out part 2

Check out part 3 (not yet available)

To paraphrase Lehohla, he disagreed with their methodology, their data and their values and ethics:

First, I need to engage the author on methods. Second, I address the facts. Third, I focus on the morality of political systems and, finally, I question the integrity of the luminaries of DaMina and ask them to come clean.

This wasn’t data I had looked at before, but some of Lehohla’s criticisms seemed valid. Using nominal GDP growth data is close to meaningless over periods of different inflation.

Second, the methodology of interpreting economic growth should use real growth instead of nominal growth because this carries with it differing inflation rates. This is to standardise the rates across high and low inflation periods.

I haven’t confirmed the DaMina calculations, but the labels in their table do say “current USD prices” which suggests they have used nominal data. It’s little wonder any period including the 1970s looks great from a nominal growth perspective with nominal USD GDP growth in 1973 and 1974 being 34% and 23%, compared to real growth of 2.2% and 3.8%. The high inflation of the 1970s arising from oil shocks and breakdown of the gold standard distorts this analysis completely.

Lehohla’s other complaint is also important, but less straightforward to my mind –

The methods that underpin any comparison for a given country cannot be based on a currency other than that of the country concerned. The reason is that exchange-rate fluctuations exaggerate the changes beyond what they actually are.

Two problems here – one is that purchasing power adjusted GDP indices are not typically available going far back in history. The other is that if one is using real GDP, the worst of the problems of currency fluctuations are already ironed out. (The worst, certainly not all and it would still be a factor that should be analysed rather than completely overlooked.)

I was disappointed that neither piece mentioned anything at all about real GDP per capita. Does it really matter how much more we produce as a country if the income per person is declining? Income inequality aside, important as it is, more GDP per capita means more earning power per person, more income per person, more things per person. It is a far more useful measure of prosperity for a country, and particularly for comparing economic growth across countries with different population growth rates.

My own analysis, based on World Bank data (available from 1960 to 2013)

I’ve put these numbers out without much analysis. However, it’s pretty clear that on the most sensible measure (real GDP per capita) over the periods the DaMina study considered, post-apartheid growth has been better than during the 1971-1990 period of Apartheid.

The conclusion is reversed if one includes the 1960s Apartheid economy and the latest data to 2013, the picture is reversed on both measures.

This, above all else, should talk to the dangers of selecting data to suit the outcome.

This analysis doesn’t talk to the impact of the gold standard, the low cost of gold mining closer to the surface than it is now, the technological catch-up South Africa should have benefited from more in the past, the impact of international sanctions and expenditure on the old SADF and who knows what else. There are much big monsters lurking there that I am not equipped to begin to analyse.

My overall conclusion? The Apartheid days were not “economically better” even without ignoring the millions of lives damaged. Unfortunately, our economic growth has for decades been too low to progress our economy to provide a better life for all.

Here is the problem:

Despite the theory of “Convergence“, the US has had double South Africa’s per capita GDP growth for over five decades.  Real GDP per capita increased by 72% in South Africa over the entire period from 1960 to 2013, which sounds impressive until you realise that the US managed 189%. That is more than 2.5x our growth Brazil has done even better at 237%. “Even Kenya” outperformed us over this period.

1% per annum real per capita GDP growth is just not good enough.

European five year inflation expectations

It really does seem that UK / US policies are, more slowly than necessary, coming right and the economies are slowly shrugging off the GFC and are moving forwards.  The rest of Europe is not.

Messages? This time isn’t different, sovereign debt crises happen all the time, ignore currency risk at your peril and there are many reasons governments can default on their debt.

But is overall domestic credit extension out of control? Are real interest rates negative? Is the global economy strong and steaming ahead?

The answer to all these questions is “no”. Here is a graph produced from public reservebank data.

The proportion of people who speak sense has declined to the lowest level recorded since ever.

“If Eskom puts up its prices too high we’ll have higher inflation. Inflation is bad therefore Eskom shouldn’t put up electricity prices so much.”

Oh really? What happens to the cost of producing electricity when Eskom puts up its prices by 16% rather than 8%? Nothing. Well actually the cost goes down, but then I’m being sneaky – raising the price will reduce consumption, which in turn will decrease the total amount of electricity produced, thus reducing the aggregate cost of electricity production. Yes, it’s sneaky because we all knew I meant the “cost per unit” of electricity.

But wait, if we consume less electricity, Eskom presumably would have to use less gas-turbine powered emergency and oh-so-very-expensive sources of electricity to fill in at peak times. So just maybe the cost per unit of electricity would go down if Eskom were allowed to raise it’s prices by 16% and not 8%.

Another good way to lower inflation would be for government to add a 1% subsidy on everything this year. Everything will be 1% cheaper because you mail (fax?) your receipts to Pravin and Government will mail you a postal order for 1% of the value back in.  Instantly effective prices are 1% lower and inflation is more under control.

Hell, why stop at 1%? Let’s have a 2% reduction.  And a further 2% next year and so on.