Some countries look more prone to rising inflation than others. From an analysis of wages, inflation expectations, demand and capacity pressures, and monetary growth, Mr Cates infers that Argentina, Brazil, India, Russia and the Middle East oil exporters face the biggest risks in the months ahead. Pressures seem less great in China, Mexico, South Korea and Turkey.

Clearly, monetary policy needs to be tightened. Instead, it has in effect been loosened: real interest rates are generally lower than they were a year ago. Short-term interest rates are also unusually low relative to nominal GDP growth a crude gauge of where rates should be, which implies that monetary policy is very loose (...). The broad money supply has grown by an average of 20% over the past year in emerging economies, almost three times the pace in the developed world (…). Russia's money supply has swelled by fully 42%.

Add all this up, and emerging economies bear strong similarities to rich countries in the 1970s, when the Great Inflation took off. A synchronised boom in the world economy has caused commodity prices to surge. Governments have responded with subsidies and wage and price controls. Official statistics understate price pressures. Economies are running at full pelt. Money-supply growth is soaring. Inflation expectations are not anchored and labour markets are fairly rigid, increasing the risk of a spiral in wages and prices.

According to conventional wisdom, the monetary-policy mistakes that caused the Great Inflation are much less likely today because central banks are independent of politicians. But unlike the Federal Reserve and the European Central Bank ECB, many central banks in emerging economies notably China, India and Russia are not fully independent. In another echo of the 1970s, they often face intense political pressure to hold rates low to boost growth and jobs.

The text remarks on:

Item 0: the existence of strong similarities between the rich countries economies in the 1970s and now;

Com relação ao teste de hipótese, é correto afirmar:

Item 4: O teste t em regressões envolvendo variáveis não-estacionárias não será válido caso a regressão seja expúria.

Seja Y_i, i = 1, ..., n, uma variável aleatória tal que Y_i = 1 com probabilidade p e Y_i = 0 com probabilidade 1-p. Defina !$ X = \sum^n _{i=1} Y_i !$. Responda se a afirmativa abaixo é verdadeira ou falsa:

Item 3: Se !$ n \rightarrow \infty !$ e p permanecer fixo, então !$ { \large X - np \over \sqrt{np (1-p)}} !$ converge para distribuição normal com média 0 e variância 1.

Considere as seqüências !$ (x_n) !$ e !$ (y_n) !$ definidas por !$ x_n= {\large n \over n!} !$ e !$ y_n= \sqrt n+1 - \sqrt n !$. Julgue a afirmativa:

Item 2: !$ lim _{n → ∞} y_n = 0 !$.