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Unemployment and the Nazis: A fatal combination?

Unemployment and the Nazis: A fatal combination?. How far do the unemployment statistics in the Weimar Republic help to explain the rise of the Nazis?. By Mr S. Drew Downloaded from www.SchoolHistory.co.uk. Unemployment and the Nazis: A fatal combination?.

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Unemployment and the Nazis: A fatal combination?

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  1. Unemployment and the Nazis: A fatal combination? How far do the unemployment statistics in the Weimar Republic help to explain the rise of the Nazis? By Mr S. Drew Downloaded from www.SchoolHistory.co.uk

  2. Unemployment and the Nazis: A fatal combination? The Nazi Party did not exist when the Weimar Republic was founded, yet by 1933 Hitler was Chancellor of Germany. One explanation of Hitler’s rise to power is to be found by analysing the relationship between unemployment in Germany and the votes received by the Nazi Party. As the statistics in the presentation will show there is a clear link between the two things. HOWEVER remember that no matter how strong and compelling the link looks you MUST try to think of the other factors that could help to explain the link and the rise of the Nazis to power.

  3. May 1924 50% In May 1924, the economic crisis in the Weimar Republic was at its height. Hyperinflation was rampant and unemployment stood at 2 million (13.5%), its peak for the period,. In this context the Nazis fought their first election and achieved a very creditable 32 seats in the Reichstag (6.7% of the total). Nazi seats Unemployment 40% 30% 20% 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  4. Nov. 1924 50% By November 1924, the economic crisis in the Weimar Republic was coming to an end. The hyperinflation had been brought under control following the introduction of the Rentenmark, and unemployment had fallen by half since May to 1 5million (6.7%). In this context the Nazi policies were far less attractive and they lost seats in the Reichstag, falling to just 14 members (2.8% of the total). Nazi seats Unemployment 40% 30% 20% 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  5. May 1928 50% In May 1928, the Weimar Republic was at its popular peak. The crisis of 1923-24 seemed only a bitter memory as the economy boomed and unemployment remained relatively low. Even though it had risen to 1.5 million (10%) since 1924, this was not seen as a huge problem. In this situation the Nazis seemed to be a spent force in elections, gaining just 12 Reichstag seats (2.4% of the total). Nazi seats Unemployment 40% 30% 20% 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  6. By September 1930, the economy of Germany was in deep depression as a result of the Wall Street Crash of November 1929 and the recall of the American loans that had propped it up. Unemployment had rocketed to 3.1 million (15.3%), and the Weimar politicians seemed incapable of solving the problems. In this situation the Nazis began to be seen as a way out, and their support rose. They gained 107 Reichstag seats (18.5% of the total). Sept. 1930 50% Nazi seats Unemployment 40% 30% 20% 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  7. By July 1932, the economic depression that followed the 1929 crash was at its peak. Unemployment had continued to rise and now stood at 5.5 million (30.1%). The faith of the German people in democracy seemed to be totally shattered. The Nazis continued their meteoric rise in popularity in this election, winning 230 Reichstag seats (37.8% of the total). July 1932 50% 40% 30% 20% 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  8. By November 1932, the economic depression was beginning to come to an end. Unemployment had started to fall, but still stood at the vast figure of 5 million (27%). It seemed as though the crisis was over. Support for the Nazis fell slightly, but they still remained the largest single party in the Reichstag by far, with 196 seats (33.5% of the total). Nov. 1932 50% Were the Nazis now a finished force? 40% 30% 20% Would falling unemployment cost them power? 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  9. The elections of March 1933 do not fit the pattern of those between 1924 and 1932. With unemployment falling (to 4.5 million or 23.3%), the trend of the graph shows us that the Nazis should have lost more seats. However their seats in the Reichstag rose to 288 or 44.5% of the total. Mar. 1933 50% WHY? 40% 30% So although the link between the level of German unemployment and Nazi votes is clear up to 1932, it breaks after that date. 20% 10% 0% May 1924 Nov. 1924 May 1928 Sept. 1930 July 1932 Nov. 1932 Mar. 1933

  10. Unemployment and the Nazis: A fatal combination? You have seen the evidence for the case that there is a direct link between the unemployment rate in the Weimar Republic and the rise of the Nazis to power. PRETTY STRONG STUFF ISN’T IT!!! BUT: You are doubtless thinking to yourself that this is not enough to explain the rise of the Nazis, and you may even have already thought of some holes in the argument and some evidence you could use to argue against what you have seen in this presentation. RIGHT! Now the task! You are going to answer this question: How far do the levels of unemployment in the Weimar Republic explain the rise of the Nazis to power?

  11. How far do the levels of unemployment in the Weimar Republic explain the rise of the Nazis to power? • Plan your answer by preparing two lists: • Evidence that the rise of the Nazis can be explained by German unemployment. • Evidence that there were other factors that led to the rise of the Nazis • When you have done this, use arrows between your lists to show how the two sets of evidence are linked together. • Write your answer using your plan as a base. Make sure you: • Provide evidence and explanation that unemployment levels DO explain the rise of the Nazis. • Provide evidence and explanation that OTHER factors are important as well. • Complete your answer by showing how the rise of the Nazis must be explained by the combination of unemployment AND other factors.

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